R-universe search: multidimensional

philchalmers

mirt:Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.

Maintained by Phil Chalmers. Last updated 11 days ago.

irt mirt openblas cpp openmp

11.1 match 210 stars 14.98 score 2.5k scripts 40 dependents

spatstat

spatstat.geom:Geometrical Functionality of the 'spatstat' Family

Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)

Maintained by Adrian Baddeley. Last updated 2 days ago.

classes-and-objects distance-calculation geometry geometry-processing images mensuration plotting point-patterns spatial-data spatial-data-analysis

12.4 match 7 stars 12.11 score 241 scripts 227 dependents

vegandevs

vegan:Community Ecology Package

Ordination methods, diversity analysis and other functions for community and vegetation ecologists.

Maintained by Jari Oksanen. Last updated 16 days ago.

ecological-modelling ecology ordination fortran openblas

6.8 match 472 stars 19.41 score 15k scripts 440 dependents

tguillerme

dispRity:Measuring Disparity

A modular package for measuring disparity (multidimensional space occupancy). Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several statistical tests for disparity analysis.

Maintained by Thomas Guillerme. Last updated 2 days ago.

disparity ecology multidimensionality palaeobiology

14.6 match 26 stars 8.69 score 220 scripts 1 dependents

clugen

clugenr:Multidimensional Cluster Generation Using Support Lines

An implementation of the clugen algorithm for generating multidimensional clusters with arbitrary distributions. Each cluster is supported by a line segment, the position, orientation and length of which guide where the respective points are placed. This package is described in Fachada & de Andrade (2023) <doi:10.1016/j.knosys.2023.110836>.

Maintained by Nuno Fachada. Last updated 7 months ago.

multidimensional-clusters multidimensional-data synthetic-clusters synthetic-data-generator synthetic-dataset-generation

20.4 match 5 stars 5.39 score 14 scripts

kisungyou

Rdimtools:Dimension Reduction and Estimation Methods

We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You and Shung (2022) <doi:10.1016/j.simpa.2022.100414>.

Maintained by Kisung You. Last updated 2 years ago.

dimension-estimation dimension-reduction manifold-learning subspace-learning openblas cpp openmp

11.9 match 52 stars 8.37 score 186 scripts 8 dependents

cran

autoRasch:Semi-Automated Rasch Analysis

Performs Rasch analysis (semi-)automatically, which has been shown to be comparable with the standard Rasch analysis (Feri Wijayanto et al. (2021) <doi:10.1111/bmsp.12218>, Feri Wijayanto et al. (2022) <doi:10.3758/s13428-022-01947-9>, Feri Wijayanto et al. (2022) <doi:10.1177/01466216221125178>).

Maintained by Feri Wijayanto. Last updated 2 years ago.

openblas cpp openmp

27.8 match 3.00 score

santagos

dad:Three-Way / Multigroup Data Analysis Through Densities

The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.

Maintained by Pierre Santagostini. Last updated 4 months ago.

14.1 match 5.33 score 92 scripts

bioc

SparseArray:High-performance sparse data representation and manipulation in R

The SparseArray package provides array-like containers for efficient in-memory representation of multidimensional sparse data in R (arrays and matrices). The package defines the SparseArray virtual class and two concrete subclasses: COO_SparseArray and SVT_SparseArray. Each subclass uses its own internal representation of the nonzero multidimensional data: the "COO layout" and the "SVT layout", respectively. SVT_SparseArray objects mimic as much as possible the behavior of ordinary matrix and array objects in base R. In particular, they suppport most of the "standard matrix and array API" defined in base R and in the matrixStats package from CRAN.

Maintained by Hervé Pagès. Last updated 24 days ago.

infrastructure datarepresentation bioconductor-package core-package openmp

5.7 match 8 stars 12.68 score 79 scripts 1.2k dependents

bioc

escheR:Unified multi-dimensional visualizations with Gestalt principles

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.

Maintained by Boyi Guo. Last updated 5 months ago.

spatial singlecell transcriptomics visualization software multidimensional single-cell spatial-omics

10.0 match 6 stars 6.74 score 153 scripts 1 dependents

cmlmagneville

mFD:Compute and Illustrate the Multiple Facets of Functional Diversity

Computing functional traits-based distances between pairs of species for species gathered in assemblages allowing to build several functional spaces. The package allows to compute functional diversity indices assessing the distribution of species (and of their dominance) in a given functional space for each assemblage and the overlap between assemblages in a given functional space, see: Chao et al. (2018) <doi:10.1002/ecm.1343>, Maire et al. (2015) <doi:10.1111/geb.12299>, Mouillot et al. (2013) <doi:10.1016/j.tree.2012.10.004>, Mouillot et al. (2014) <doi:10.1073/pnas.1317625111>, Ricotta and Szeidl (2009) <doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included. Visit the 'mFD' website for more information, documentation and examples.

Maintained by Camille Magneville. Last updated 3 months ago.

9.1 match 26 stars 7.35 score 61 scripts

tsellam

findviews:A View Generator for Multidimensional Data

A tool to explore wide data sets, by detecting, ranking and plotting groups of statistically dependent columns.

Maintained by Thibault Sellam. Last updated 5 years ago.

13.7 match 40 stars 4.38 score 12 scripts

herveabdi

DistatisR:DiSTATIS Three Way Metric Multidimensional Scaling

Implement DiSTATIS and CovSTATIS (three-way multidimensional scaling). DiSTATIS and CovSTATIS are used to analyze multiple distance/covariance matrices collected on the same set of observations. These methods are based on Abdi, H., Williams, L.J., Valentin, D., & Bennani-Dosse, M. (2012) <doi:10.1002/wics.198>.

Maintained by Herve Abdi. Last updated 1 years ago.

3-way-mds distatis metric-multidimensional-scaling

13.4 match 4 stars 4.42 score 44 scripts

corybrunson

ordr:A Tidyverse Extension for Ordinations and Biplots

Ordination comprises several multivariate exploratory and explanatory techniques with theoretical foundations in geometric data analysis; see Podani (2000, ISBN:90-5782-067-6) for techniques and applications and Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0> for foundations. Greenacre (2010, ISBN:978-84-923846) shows how the most established of these, including principal components analysis, correspondence analysis, multidimensional scaling, factor analysis, and discriminant analysis, rely on eigen-decompositions or singular value decompositions of pre-processed numeric matrix data. These decompositions give rise to a set of shared coordinates along which the row and column elements can be measured. The overlay of their scatterplots on these axes, introduced by Gabriel (1971) <doi:10.1093/biomet/58.3.453>, is called a biplot. 'ordr' provides inspection, extraction, manipulation, and visualization tools for several popular ordination classes supported by a set of recovery methods. It is inspired by and designed to integrate into 'tidyverse' workflows provided by Wickham et al (2019) <doi:10.21105/joss.01686>.

Maintained by Jason Cory Brunson. Last updated 13 days ago.

biplot data-visualization dimension-reduction geometric-data-analysis grammar-of-graphics log-ratio-analysis multivariate-analysis multivariate-statistics ordination tidymodels tidyverse

8.1 match 24 stars 7.26 score 28 scripts

alexanderrobitzsch

sirt:Supplementary Item Response Theory Models

Supplementary functions for item response models aiming to complement existing R packages. The functionality includes among others multidimensional compensatory and noncompensatory IRT models (Reckase, 2009, <doi:10.1007/978-0-387-89976-3>), MCMC for hierarchical IRT models and testlet models (Fox, 2010, <doi:10.1007/978-1-4419-0742-4>), NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>), Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>; Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>), faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, <doi:10.1111/j.1745-3984.2011.00143.x>), ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>), DETECT statistic (Stout, Habing, Douglas & Kim, 1996, <doi:10.1177/014662169602000403>), local structural equation modeling (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, <doi:10.1080/00273171.2016.1142856>).

Maintained by Alexander Robitzsch. Last updated 3 months ago.

item-response-theory openblas cpp

5.8 match 23 stars 10.01 score 280 scripts 22 dependents

mlysy

nicheROVER:Niche Region and Niche Overlap Metrics for Multidimensional Ecological Niches

Implementation of a probabilistic method to calculate 'nicheROVER' (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology. See the package vignette for a worked example using fish stable isotope data.

Maintained by Martin Lysy. Last updated 1 years ago.

8.0 match 9 stars 6.80 score 47 scripts 1 dependents

cran

ClimProjDiags:Set of Tools to Compute Various Climate Indices

Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices.

Maintained by Victòria Agudetse. Last updated 1 years ago.

10.5 match 5.14 score 58 scripts 4 dependents

hojsgaard

gRbase:A Package for Graphical Modelling in R

The 'gRbase' package provides graphical modelling features used by e.g. the packages 'gRain', 'gRim' and 'gRc'. 'gRbase' implements graph algorithms including (i) maximum cardinality search (for marked and unmarked graphs). (ii) moralization, (iii) triangulation, (iv) creation of junction tree. 'gRbase' facilitates array operations, 'gRbase' implements functions for testing for conditional independence. 'gRbase' illustrates how hierarchical log-linear models may be implemented and describes concept of graphical meta data. The facilities of the package are documented in the book by Højsgaard, Edwards and Lauritzen (2012, <doi:10.1007/978-1-4614-2299-0>) and in the paper by Dethlefsen and Højsgaard, (2005, <doi:10.18637/jss.v014.i17>). Please see 'citation("gRbase")' for citation details.

Maintained by Søren Højsgaard. Last updated 4 months ago.

openblas cpp

5.8 match 3 stars 9.24 score 241 scripts 20 dependents

jojo-

mipfp:Multidimensional Iterative Proportional Fitting and Alternative Models

An implementation of the iterative proportional fitting (IPFP), maximum likelihood, minimum chi-square and weighted least squares procedures for updating a N-dimensional array with respect to given target marginal distributions (which, in turn can be multidimensional). The package also provides an application of the IPFP to simulate multivariate Bernoulli distributions.

Maintained by Johan Barthelemy. Last updated 4 years ago.

7.1 match 24 stars 6.79 score 86 scripts 3 dependents

philchalmers

mirtCAT:Computerized Adaptive Testing with Multidimensional Item Response Theory

Provides tools to generate HTML interfaces for adaptive and non-adaptive tests using the shiny package (Chalmers (2016) <doi:10.18637/jss.v071.i05>). Suitable for applying unidimensional and multidimensional computerized adaptive tests (CAT) using item response theory methodology and for creating simple questionnaires forms to collect response data directly in R. Additionally, optimal test designs (e.g., "shadow testing") are supported for tests that contain a large number of item selection constraints. Finally, package contains tools useful for performing Monte Carlo simulations for studying test item banks.

Maintained by Phil Chalmers. Last updated 5 months ago.

cat irt openblas cpp

5.1 match 95 stars 9.41 score 62 scripts 3 dependents

drwolf85

spMC:Continuous-Lag Spatial Markov Chains

A set of functions is provided for 1) the stratum lengths analysis along a chosen direction, 2) fast estimation of continuous lag spatial Markov chains model parameters and probability computing (also for large data sets), 3) transition probability maps and transiograms drawing, 4) simulation methods for categorical random fields. More details on the methodology are discussed in Sartore (2013) <doi:10.32614/RJ-2013-022> and Sartore et al. (2016) <doi:10.1016/j.cageo.2016.06.001>.

Maintained by Luca Sartore. Last updated 2 years ago.

openblas openmp

16.3 match 3 stars 2.92 score 55 scripts

fauvernierma

survPen:Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models

Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (thanks to explicit calculation of the derivatives of the likelihood) and offers a unified framework for multidimensional penalized hazard and excess hazard models. Later versions (>2.0.0) include penalized models for relative mortality ratio, and marginal intensity in recurrent event setting. survPen may be of interest to those who 1) analyse any kind of time-to-event data: mortality, disease relapse, machinery breakdown, unemployment, etc 2) wish to describe the associated hazard and to understand which predictors impact its dynamics, 3) wish to model the relative mortality ratio between a cohort and a reference population, 4) wish to describe the marginal intensity for recurrent event data. See Fauvernier et al. (2019a) <doi:10.21105/joss.01434> for an overview of the package and Fauvernier et al. (2019b) <doi:10.1111/rssc.12368> for the method.

Maintained by Mathieu Fauvernier. Last updated 4 months ago.

cpp

6.8 match 12 stars 6.82 score 85 scripts 1 dependents

girelaignacio

mpitbR:Calculate Alkire-Foster Multidimensional Poverty Measures

Estimate Multidimensional Poverty Indices disaggregated by population subgroups based on the Alkire and Foster method (2011) <doi:10.1016/j.jpubeco.2010.11.006>. This includes the calculation of standard errors and confidence intervals. Other partial indices such as incidence, intensity and indicator-specific measures as well as intertemporal changes analysis can also be estimated. The standard errors and confidence intervals are calculated considering the complex survey design.

Maintained by Ignacio Girela. Last updated 1 months ago.

9.4 match 4.85 score 1 scripts

tplate

abind:Combine Multidimensional Arrays

Combine multidimensional arrays into a single array. This is a generalization of 'cbind' and 'rbind'. Works with vectors, matrices, and higher-dimensional arrays (aka tensors). Also provides functions 'adrop', 'asub', and 'afill' for manipulating, extracting and replacing data in arrays.

Maintained by Tony Plate. Last updated 6 months ago.

3.9 match 1 stars 11.34 score 5.7k scripts 3.4k dependents

cadam00

prior3D:3D Prioritization Algorithm

Three-dimensional systematic conservation planning, conducting nested prioritization analyses across multiple depth levels and ensuring efficient resource allocation throughout the water column. It provides a structured workflow designed to address biodiversity conservation and management challenges in the 3 dimensions, while facilitating users’ choices and parameterization (Doxa et al. 2025 <doi:10.1016/j.ecolmodel.2024.110919>).

Maintained by Christos Adam. Last updated 2 months ago.

biodiversity conservation conservation-planning depth marine-spatial-planning multidimensional-environments prioritization

7.5 match 6 stars 5.62 score 3 scripts

thomasp85

ambient:A Generator of Multidimensional Noise

Generation of natural looking noise has many application within simulation, procedural generation, and art, to name a few. The 'ambient' package provides an interface to the 'FastNoise' C++ library and allows for efficient generation of perlin, simplex, worley, cubic, value, and white noise with optional perturbation in either 2, 3, or 4 (in case of simplex and white noise) dimensions.

Maintained by Thomas Lin Pedersen. Last updated 3 years ago.

cpp

5.2 match 97 stars 8.09 score 956 scripts 2 dependents

luca-scr

mclust:Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

Maintained by Luca Scrucca. Last updated 11 months ago.

fortran openblas

3.4 match 21 stars 12.23 score 6.6k scripts 587 dependents

bioc

S4Arrays:Foundation of array-like containers in Bioconductor

The S4Arrays package defines the Array virtual class to be extended by other S4 classes that wish to implement a container with an array-like semantic. It also provides: (1) low-level functionality meant to help the developer of such container to implement basic operations like display, subsetting, or coercion of their array-like objects to an ordinary matrix or array, and (2) a framework that facilitates block processing of array-like objects (typically on-disk objects).

Maintained by Hervé Pagès. Last updated 1 months ago.

infrastructure datarepresentation bioconductor-package core-package

3.8 match 5 stars 10.99 score 8 scripts 1.2k dependents

mattmar

rasterdiv:Diversity Indices for Numerical Matrices

Provides methods to calculate diversity indices on numerical matrices based on information theory, as described in Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039>, and Rocchini et al. (2021) <doi:10.1101/2021.01.23.427872>.

Maintained by Matteo Marcantonio. Last updated 20 days ago.

5.2 match 15 stars 7.65 score 44 scripts 1 dependents

igraph

igraph:Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

Maintained by Kirill Müller. Last updated 15 hours ago.

complex-networks graph-algorithms graph-theory mathematics network-analysis network-graph fortran libxml2 glpk openblas cpp

1.9 match 582 stars 21.11 score 31k scripts 1.9k dependents

uchidamizuki

dibble:Dimensional Data Frames

Provides a 'dibble' that implements data cubes (derived from 'dimensional tibble'), and allows broadcasting by dimensional names.

Maintained by Mizuki Uchida. Last updated 29 days ago.

multidimensional-arrays tidy-data

7.5 match 14 stars 5.05 score 8 scripts

bocaccio

plink:IRT Separate Calibration Linking Methods

Item response theory based methods are used to compute linking constants and conduct chain linking of unidimensional or multidimensional tests for multiple groups under a common item design. The unidimensional methods include the Mean/Mean, Mean/Sigma, Haebara, and Stocking-Lord methods for dichotomous (1PL, 2PL and 3PL) and/or polytomous (graded response, partial credit/generalized partial credit, nominal, and multiple-choice model) items. The multidimensional methods include the least squares method and extensions of the Haebara and Stocking-Lord method using single or multiple dilation parameters for multidimensional extensions of all the unidimensional dichotomous and polytomous item response models. The package also includes functions for importing item and/or ability parameters from common IRT software, conducting IRT true score and observed score equating, and plotting item response curves/surfaces, vector plots, information plots, and comparison plots for examining parameter drift.

Maintained by Jonathan P. Weeks. Last updated 8 years ago.

8.3 match 2 stars 4.58 score 44 scripts 1 dependents

cran

CSIndicators:Climate Services' Indicators Based on Sub-Seasonal to Decadal Predictions

Set of generalised tools for the flexible computation of climate related indicators defined by the user. Each method represents a specific mathematical approach which is combined with the possibility to select an arbitrary time period to define the indicator. This enables a wide range of possibilities to tailor the most suitable indicator for each particular climate service application (agriculture, food security, energy, water management, ...). This package is intended for sub-seasonal, seasonal and decadal climate predictions, but its methods are also applicable to other time-scales, provided the dimensional structure of the input is maintained. Additionally, the outputs of the functions in this package are compatible with 'CSTools'. This package is described in 'Pérez-Zanón et al. (2023) <doi:10.1016/j.cliser.2023.100393>' and it was developed in the context of 'H2020 MED-GOLD' (776467) and 'S2S4E' (776787) projects. See 'Lledó et al. (2019) <doi:10.1016/j.renene.2019.04.135>' and 'Chou et al., 2023 <doi:10.1016/j.cliser.2023.100345>' for details.

Maintained by Victòria Agudetse. Last updated 1 years ago.

12.5 match 3.00 score 6 scripts

naidantu

bmggum:Bayesian Multidimensional Generalized Graded Unfolding Model

Full Bayesian estimation of Multidimensional Generalized Graded Unfolding Model (MGGUM) using 'rstan' (See Stan Development Team (2020) <https://mc-stan.org/>). Functions are provided for estimation, result extraction, model fit statistics, and plottings.

Maintained by Naidan Tu. Last updated 3 years ago.

cpp openjdk

8.0 match 5 stars 4.40 score 5 scripts

pmair78

smacof:Multidimensional Scaling

Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.

Maintained by Patrick Mair. Last updated 5 months ago.

4.3 match 5 stars 7.86 score 152 scripts 24 dependents

andrisignorell

DescTools:Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

Maintained by Andri Signorell. Last updated 11 hours ago.

fortran cpp

2.0 match 87 stars 16.70 score 7.7k scripts 99 dependents

yannabraham

Radviz:Project Multidimensional Data in 2D Space

An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Ankerst *et al.* (1996) (<https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.1811>) for original implementation, see Di Caro *et al* (2012) (<https://link.springer.com/chapter/10.1007/978-3-642-13672-6_13>) for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.

Maintained by Yann Abraham. Last updated 3 years ago.

high-dimensional-data radviz science visualization cpp

5.4 match 10 stars 6.19 score 52 scripts

appelmar

gdalcubes:Earth Observation Data Cubes from Satellite Image Collections

Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, plotting, and extraction from spatial and or spatiotemporal features. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.

Maintained by Marius Appel. Last updated 1 years ago.

remote-sensing satellite-imagery spatial-analysis gdal netcdf cpp

3.8 match 124 stars 8.39 score 356 scripts

mikewlcheung

metaSEM:Meta-Analysis using Structural Equation Modeling

A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices, see Cheung (2015) <doi:10.3389/fpsyg.2014.01521>.

Maintained by Mike Cheung. Last updated 10 days ago.

meta-analysis meta-analytic-sem missing-data multilevel-models multivariate-analysis structural-equation-modeling structural-equation-models

3.3 match 30 stars 9.43 score 208 scripts 1 dependents

shabbychef

madness:Automatic Differentiation of Multivariate Operations

An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.

Maintained by Steven E. Pav. Last updated 4 years ago.

4.7 match 31 stars 6.59 score 28 scripts 3 dependents

josesamos

geomultistar:Multidimensional Queries Enriched with Geographic Data

Multidimensional systems allow complex queries to be carried out in an easy way. The geographical dimension, together with the temporal dimension, plays a fundamental role in multidimensional systems. Through this package, vector geographic data layers can be associated to the attributes of geographic dimensions, so that the results of multidimensional queries can be obtained directly as vector layers. The multidimensional structures on which we can define the queries can be created from a flat table or imported directly using functions from this package.

Maintained by Jose Samos. Last updated 8 months ago.

6.9 match 2 stars 4.48 score 8 scripts 1 dependents

r-spatial

stars:Spatiotemporal Arrays, Raster and Vector Data Cubes

Reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in 'R', using 'GDAL' bindings provided by 'sf', and 'NetCDF' bindings by 'ncmeta' and 'RNetCDF'.

Maintained by Edzer Pebesma. Last updated 30 days ago.

raster satellite-images spatial

1.7 match 571 stars 18.27 score 7.2k scripts 137 dependents

slzhang-fd

mirtjml:Joint Maximum Likelihood Estimation for High-Dimensional Item Factor Analysis

Provides constrained joint maximum likelihood estimation algorithms for item factor analysis (IFA) based on multidimensional item response theory models. So far, we provide functions for exploratory and confirmatory IFA based on the multidimensional two parameter logistic (M2PL) model for binary response data. Comparing with traditional estimation methods for IFA, the methods implemented in this package scale better to data with large numbers of respondents, items, and latent factors. The computation is facilitated by multiprocessing 'OpenMP' API. For more information, please refer to: 1. Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23. <doi:10.1007/s11336-018-9646-5>; 2. Chen, Y., Li, X., & Zhang, S. (2019). Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications. Journal of the American Statistical Association, <doi: 10.1080/01621459.2019.1635485>.

Maintained by Siliang Zhang. Last updated 4 years ago.

ifa item-factor-analysis large-scale-assessment parallel-computing psychometrics openblas cpp openmp

7.3 match 9 stars 4.21 score 12 scripts 1 dependents

virgesmith

humanleague:Synthetic Population Generator

Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) <doi:10.18564/jasss.3550>). The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) <doi:10.13140/2.1.2480.9923>).

Maintained by Andrew Smith. Last updated 5 months ago.

c-plus-plus-11 microsynthesis nodejs python3 quasirandom sampling-methods cpp

6.1 match 18 stars 4.99 score 12 scripts

berriez

asymmetry:Multidimensional Scaling of Asymmetric Proximities

Multidimensional scaling models and methods for the visualization and analysis of asymmetric proximity data<doi:10.1111/j.2044-8317.1996.tb01078.x>. An asymmetric data matrix has the same number of rows and columns, and these rows and columns refer to the same set of objects. At least some elements in the upper-triangle are different from the corresponding elements in the lower triangle. An example of an asymmetric matrix is a student migration table, where the rows correspond to the countries of origin of the students and the columns to the destination countries. This package provides algorithms for three multidimensional scaling models. These are the slide-vector model<doi:10.1007/BF02294474>, a scaling model with unique dimensions and the asymscal model for asymmetric multidimensional scaling. Furthermore, a heat map for skew-symmetric data, and the decomposition of asymmetry are provided for the exploratory analysis of asymmetric tables.

Maintained by Berrie Zielman. Last updated 9 months ago.

7.8 match 3.78 score 12 scripts

momx

Momocs:Morphometrics using R

The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.

Maintained by Vincent Bonhomme. Last updated 1 years ago.

morphometrics

3.9 match 51 stars 7.42 score 346 scripts

thomasp85

ggraph:An Implementation of Grammar of Graphics for Graphs and Networks

The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.

Maintained by Thomas Lin Pedersen. Last updated 1 years ago.

ggplot-extension ggplot2 graph-visualization network-visualization visualization cpp

1.7 match 1.1k stars 16.96 score 9.2k scripts 111 dependents

stla

polyhedralCubature:Multiple Integration over Convex Polyhedra

Evaluation of multiple integrals over convex polyhedra. This is useful when the bounds of the integrals are some linear combinations of the variables.

Maintained by Stéphane Laurent. Last updated 1 years ago.

integration multidimensional-integration

7.5 match 3.70 score 4 scripts

modal-inria

Rankcluster:Model-Based Clustering for Multivariate Partial Ranking Data

Implementation of a model-based clustering algorithm for ranking data (C. Biernacki, J. Jacques (2013) <doi:10.1016/j.csda.2012.08.008>). Multivariate rankings as well as partial rankings are taken into account. This algorithm is based on an extension of the Insertion Sorting Rank (ISR) model for ranking data, which is a meaningful and effective model parametrized by a position parameter (the modal ranking, quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity of the rank population is modelled by a mixture of ISR, whereas conditional independence assumption is considered for multivariate rankings.

Maintained by Quentin Grimonprez. Last updated 2 years ago.

clustering hacktoberfest rank cpp

7.3 match 1 stars 3.74 score 37 scripts 1 dependents

choi-phd

MAT:Multidimensional Adaptive Testing

Simulates Multidimensional Adaptive Testing using the multidimensional three-parameter logistic model as described in Segall (1996) <doi:10.1007/BF02294343>, van der Linden (1999) <doi:10.3102/10769986024004398>, Reckase (2009) <doi:10.1007/978-0-387-89976-3>, and Mulder & van der Linden (2009) <doi:10.1007/s11336-008-9097-5>.

Maintained by Seung W. Choi. Last updated 10 months ago.

openblas cpp

7.9 match 3.40 score 50 scripts

pvermees

IsoplotR:Statistical Toolbox for Radiometric Geochronology

Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.

Maintained by Pieter Vermeesch. Last updated 1 months ago.

2.8 match 69 stars 9.08 score 95 scripts 6 dependents

antoinelucas64

amap:Another Multidimensional Analysis Package

Tools for Clustering and Principal Component Analysis (With robust methods, and parallelized functions).

Maintained by Antoine Lucas. Last updated 5 months ago.

fortran cpp

3.1 match 7.66 score 460 scripts 26 dependents

bioc

limma:Linear Models for Microarray and Omics Data

Data analysis, linear models and differential expression for omics data.

Maintained by Gordon Smyth. Last updated 6 days ago.

exonarray geneexpression transcription alternativesplicing differentialexpression differentialsplicing genesetenrichment dataimport bayesian clustering regression timecourse microarray micrornaarray mrnamicroarray onechannel proprietaryplatforms twochannel sequencing rnaseq batcheffect multiplecomparison normalization preprocessing qualitycontrol biomedicalinformatics cellbiology cheminformatics epigenetics functionalgenomics genetics immunooncology metabolomics proteomics systemsbiology transcriptomics

1.7 match 13.81 score 16k scripts 585 dependents

yng-me

mpindex:Multidimensional Poverty Index (MPI)

A set of easy-to-use functions for computing the Multidimensional Poverty Index (MPI).

Maintained by Bhas Abdulsamad. Last updated 1 years ago.

5.5 match 4 stars 4.30 score 6 scripts

revelle

psych:Procedures for Psychological, Psychometric, and Personality Research

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

Maintained by William Revelle. Last updated 3 months ago.

1.7 match 52 stars 13.94 score 29k scripts 317 dependents

josesamos

rolap:Obtaining Star Databases from Flat Tables

Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.

Maintained by Jose Samos. Last updated 1 years ago.

openjdk

3.8 match 5 stars 6.12 score 25 scripts 1 dependents

haghbinh

ReMFPCA:Regularized Multivariate Functional Principal Component Analysis

Methods and tools for implementing regularized multivariate functional principal component analysis ('ReMFPCA') for multivariate functional data whose variables might be observed over different dimensional domains. 'ReMFPCA' is an object-oriented interface leveraging the extensibility and scalability of R6. It employs a parameter vector to control the smoothness of each functional variable. By incorporating smoothness constraints as penalty terms within a regularized optimization framework, 'ReMFPCA' generates smooth multivariate functional principal components, offering a concise and interpretable representation of the data. For detailed information on the methods and techniques used in 'ReMFPCA', please refer to Haghbin et al. (2023) <doi:10.48550/arXiv.2306.13980>.

Maintained by Hossein Haghbin. Last updated 2 months ago.

7.0 match 4 stars 3.30 score

bioc

edgeR:Empirical Analysis of Digital Gene Expression Data in R

Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.

Maintained by Yunshun Chen. Last updated 6 days ago.

alternativesplicing batcheffect bayesian biomedicalinformatics cellbiology chipseq clustering coverage differentialexpression differentialmethylation differentialsplicing dnamethylation epigenetics functionalgenomics geneexpression genesetenrichment genetics immunooncology multiplecomparison normalization pathways proteomics qualitycontrol regression rnaseq sage sequencing singlecell systemsbiology timecourse transcription transcriptomics openblas

1.7 match 13.40 score 17k scripts 255 dependents

thothorn

HSAUR3:A Handbook of Statistical Analyses Using R (3rd Edition)

Functions, data sets, analyses and examples from the third edition of the book ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S. Everitt, Chapman & Hall/CRC, 2014). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, Sweave source code for slides of selected chapters is included in this package (see HSAUR3/inst/slides). The publishers web page is '<https://www.routledge.com/A-Handbook-of-Statistical-Analyses-using-R/Hothorn-Everitt/p/book/9781482204582>'.

Maintained by Torsten Hothorn. Last updated 7 months ago.

3.3 match 6 stars 6.72 score 120 scripts 2 dependents

erictleung

pixarfilms:Pixar Films and Achievements

Data about Disney Pixar films provided by Wikipedia. This package contains data about the films, the people involved, and their awards.

Maintained by Eric Leung. Last updated 1 days ago.

data data-science datapackage disney imdb imdb-dataset pixar pixar-films web-scraping wikipedia

3.0 match 20 stars 7.42 score 23 scripts 1 dependents

kisungyou

maotai:Tools for Matrix Algebra, Optimization and Inference

Matrix is an universal and sometimes primary object/unit in applied mathematics and statistics. We provide a number of algorithms for selected problems in optimization and statistical inference. For general exposition to the topic with focus on statistical context, see the book by Banerjee and Roy (2014, ISBN:9781420095388).

Maintained by Kisung You. Last updated 23 hours ago.

openblas cpp openmp

4.0 match 8 stars 5.51 score 15 scripts 9 dependents

nicolas-robette

seqhandbook:Miscellaneous Tools for Sequence Analysis

It provides miscellaneous sequence analysis functions for describing episodes in individual sequences, measuring association between domains in multidimensional sequence analysis (see Piccarreta (2017) <doi:10.1177/0049124115591013>), heat maps of sequence data, Globally Interdependent Multidimensional Sequence Analysis (see Robette et al (2015) <doi:10.1177/0081175015570976>), smoothing sequences for index plots (see Piccarreta (2012) <doi:10.1177/0049124112452394>), coding sequences for Qualitative Harmonic Analysis (see Deville (1982)), measuring stress from multidimensional scaling factors (see Piccarreta and Lior (2010) <doi:10.1111/j.1467-985X.2009.00606.x>), symmetrical (or canonical) Partial Least Squares (see Bry (1996)).

Maintained by Nicolas Robette. Last updated 2 years ago.

4.5 match 6 stars 4.76 score 19 scripts

swampthingpaul

NADA2:Data Analysis for Censored Environmental Data

Contains methods described by Dennis Helsel in his book "Statistics for Censored Environmental Data using Minitab and R" (2011) and courses and videos at <https://practicalstats.com>. This package adds new functions to the `NADA` Package.

Maintained by Paul Julian. Last updated 6 months ago.

3.4 match 15 stars 6.16 score 16 scripts

fchamroukhi

samurais:Statistical Models for the Unsupervised Segmentation of Time-Series ('SaMUraiS')

Provides a variety of original and flexible user-friendly statistical latent variable models and unsupervised learning algorithms to segment and represent time-series data (univariate or multivariate), and more generally, longitudinal data, which include regime changes. 'samurais' is built upon the following packages, each of them is an autonomous time-series segmentation approach: Regression with Hidden Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'), Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise regression ('PWR'). For the advantages/differences of each of them, the user is referred to our mentioned paper references. These models are originally introduced and written in 'Matlab' by Faicel Chamroukhi <https://github.com/fchamroukhi?&tab=repositories&q=time-series&type=public&language=matlab>.

Maintained by Florian Lecocq. Last updated 5 years ago.

artificial-intelligence change-point-detection data-science dynamic-programming em-algorithm hidden-markov-models hidden-process-regression human-activity-recognition latent-variable-models model-selection multivariate-timeseries newton-raphson piecewise-regression statistical-inference statistical-learning time-series-analysis time-series-clustering openblas cpp

3.4 match 12 stars 6.18 score 28 scripts

thothorn

HSAUR:A Handbook of Statistical Analyses Using R (1st Edition)

Functions, data sets, analyses and examples from the book ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2006). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available.

Maintained by Torsten Hothorn. Last updated 3 years ago.

3.3 match 6.07 score 253 scripts 5 dependents

christinehohensinn

pcIRT:IRT Models for Polytomous and Continuous Item Responses

Estimates the multidimensional polytomous Rasch model (Rasch, 1961) and the Continuous Rating Scale model (Mueller, 1987).

Maintained by Christine Hohensinn. Last updated 7 years ago.

cpp

5.7 match 5 stars 3.54 score 14 scripts

cddesja

profileR:Profile Analysis of Multivariate Data in R

A suite of multivariate methods and data visualization tools to implement profile analysis and cross-validation techniques described in Davison & Davenport (2002) <DOI: 10.1037/1082-989X.7.4.468>, Bulut (2013), and other published and unpublished resources. The package includes routines to perform criterion-related profile analysis, profile analysis via multidimensional scaling, moderated profile analysis, generalizability theory, profile analysis by group, and a within-person factor model to derive score profiles.

Maintained by Christopher David Desjardins. Last updated 2 years ago.

3.5 match 3 stars 5.65 score 50 scripts

cran

MASS:Support Functions and Datasets for Venables and Ripley's MASS

Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).

Maintained by Brian Ripley. Last updated 16 days ago.

1.8 match 19 stars 10.53 score 11k dependents

shaelebrown

TDApplied:Machine Learning and Inference for Topological Data Analysis

Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. The main tool of topological data analysis is persistent homology, which computes a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference, and these functions can also interface with other data science packages to form flexible and integrated topological data analysis pipelines.

Maintained by Shael Brown. Last updated 5 months ago.

cpp

2.9 match 16 stars 6.60 score 8 scripts

frederic-santos

AnthropMMD:An R Package for the Mean Measure of Divergence (MMD)

Offers a graphical user interface for the calculation of the mean measure of divergence, with facilities for trait selection and graphical representations <doi:10.1002/ajpa.23336>.

Maintained by Frédéric Santos. Last updated 1 years ago.

4.8 match 3.90 score 16 scripts

phiala

ecodist:Dissimilarity-Based Functions for Ecological Analysis

Dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community ecological data. The original package description is in Goslee and Urban (2007) <doi:10.18637/jss.v022.i07>, with further statistical detail in Goslee (2010) <doi:10.1007/s11258-009-9641-0>.

Maintained by Sarah Goslee. Last updated 1 years ago.

openblas

1.9 match 9 stars 9.84 score 566 scripts 9 dependents

cran

bios2mds:From Biological Sequences to Multidimensional Scaling

Utilities dedicated to the analysis of biological sequences by metric MultiDimensional Scaling with projection of supplementary data. It contains functions for reading multiple sequence alignment files, calculating distance matrices, performing metric multidimensional scaling and visualizing results.

Maintained by Marie Chabbert. Last updated 5 years ago.

9.7 match 1 stars 1.90 score

thothorn

HSAUR2:A Handbook of Statistical Analyses Using R (2nd Edition)

Functions, data sets, analyses and examples from the second edition of the book ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2008). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, the package contains Sweave code for producing slides for selected chapters (see HSAUR2/inst/slides).

Maintained by Torsten Hothorn. Last updated 2 years ago.

3.3 match 5.51 score 181 scripts 1 dependents

anchiho

multiApply:Apply Functions to Multiple Multidimensional Arrays or Vectors

The base apply function and its variants, as well as the related functions in the 'plyr' package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The 'multiApply' package extends this paradigm with its only function, Apply, which efficiently applies functions taking one or a list of multiple unidimensional or multidimensional arrays (or combinations thereof) as input. The input arrays can have different numbers of dimensions as well as different dimension lengths, and the applied function can return one or a list of unidimensional or multidimensional arrays as output. This saves development time by preventing the R user from writing often error-prone and memory-inefficient loops dealing with multiple complex arrays. Also, a remarkable feature of Apply is the transparent use of multi-core through its parameter 'ncores'. In contrast to the base apply function, this package suggests the use of 'target dimensions' as opposite to the 'margins' for specifying the dimensions relevant to the function to be applied.

Maintained by An-Chi Ho. Last updated 2 years ago.

5.4 match 1 stars 3.32 score 28 scripts 5 dependents

jobnmadu

Dyn4cast:Dynamic Modeling and Machine Learning Environment

Estimates, predict and forecast dynamic models as well as Machine Learning metrics which assists in model selection for further analysis. The package also have capabilities to provide tools and metrics that are useful in machine learning and modeling. For example, there is quick summary, percent sign, Mallow's Cp tools and others. The ecosystem of this package is analysis of economic data for national development. The package is so far stable and has high reliability and efficiency as well as time-saving.

Maintained by Job Nmadu. Last updated 13 hours ago.

data-science equal-lenght-forecast forecasting knots machine-learning nigeria prediction regression-models spline-models statistics time-series

3.6 match 4 stars 5.03 score 38 scripts

cran

MultiLCIRT:Multidimensional Latent Class Item Response Theory Models

Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parameterizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version (since 2.1).

Maintained by Francesco Bartolucci. Last updated 8 years ago.

fortran

10.1 match 1 stars 1.78 score 2 dependents

jeffreyevans

spatialEco:Spatial Analysis and Modelling Utilities

Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.

Maintained by Jeffrey S. Evans. Last updated 13 days ago.

biodiversity conservation ecology r-spatial raster spatial vector

1.9 match 110 stars 9.55 score 736 scripts 2 dependents

tlverse

sl3:Pipelines for Machine Learning and Super Learning

A modern implementation of the Super Learner prediction algorithm, coupled with a general purpose framework for composing arbitrary pipelines for machine learning tasks.

Maintained by Jeremy Coyle. Last updated 4 months ago.

data-science ensemble-learning ensemble-model machine-learning model-selection regression stacking statistics

1.8 match 100 stars 9.94 score 748 scripts 7 dependents

anchiho

easyNCDF:Tools to Easily Read/Write NetCDF Files into/from Multidimensional R Arrays

Set of wrappers for the 'ncdf4' package to simplify and extend its reading/writing capabilities into/from multidimensional R arrays.

Maintained by An-Chi Ho. Last updated 2 years ago.

5.1 match 3.51 score 27 scripts 4 dependents

r-forge

CHNOSZ:Thermodynamic Calculations and Diagrams for Geochemistry

An integrated set of tools for thermodynamic calculations in aqueous geochemistry and geobiochemistry. Functions are provided for writing balanced reactions to form species from user-selected basis species and for calculating the standard molal properties of species and reactions, including the standard Gibbs energy and equilibrium constant. Calculations of the non-equilibrium chemical affinity and equilibrium chemical activity of species can be portrayed on diagrams as a function of temperature, pressure, or activity of basis species; in two dimensions, this gives a maximum affinity or predominance diagram. The diagrams have formatted chemical formulas and axis labels, and water stability limits can be added to Eh-pH, oxygen fugacity- temperature, and other diagrams with a redox variable. The package has been developed to handle common calculations in aqueous geochemistry, such as solubility due to complexation of metal ions, mineral buffers of redox or pH, and changing the basis species across a diagram ("mosaic diagrams"). CHNOSZ also implements a group additivity algorithm for the standard thermodynamic properties of proteins.

Maintained by Jeffrey Dick. Last updated 9 days ago.

fortran

1.9 match 9.46 score 238 scripts 4 dependents

a-dudek-ue

mdsOpt:Searching for Optimal MDS Procedure for Metric and Interval-Valued Data

Selecting the optimal multidimensional scaling (MDS) procedure for metric data via metric MDS (ratio, interval, mspline) and nonmetric MDS (ordinal). Selecting the optimal multidimensional scaling (MDS) procedure for interval-valued data via metric MDS (ratio, interval, mspline).Selecting the optimal multidimensional scaling procedure for interval-valued data by varying all combinations of normalization and optimization methods.Selecting the optimal MDS procedure for statistical data referring to the evaluation of tourist attractiveness of Lower Silesian counties. (Borg, I., Groenen, P.J.F., Mair, P. (2013) <doi:10.1007/978-3-642-31848-1>, Walesiak, M. (2016) <doi:10.15611/ekt.2016.2.01>, Walesiak, M. (2017) <doi:10.15611/ekt.2017.3.01>).

Maintained by Andrzej Dudek. Last updated 1 years ago.

7.8 match 2.28 score 19 scripts

bioc

CluMSID:Clustering of MS2 Spectra for Metabolite Identification

CluMSID is a tool that aids the identification of features in untargeted LC-MS/MS analysis by the use of MS2 spectra similarity and unsupervised statistical methods. It offers functions for a complete and customisable workflow from raw data to visualisations and is interfaceable with the xmcs family of preprocessing packages.

Maintained by Tobias Depke. Last updated 5 months ago.

metabolomics preprocessing clustering

2.9 match 10 stars 6.04 score 22 scripts

nanxstats

protr:Generating Various Numerical Representation Schemes for Protein Sequences

Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042>. For full functionality, the software 'ncbi-blast+' is needed, see <https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html> for more information.

Maintained by Nan Xiao. Last updated 6 months ago.

bioinformatics feature-engineering feature-extraction machine-learning peptides protein-sequences sequence-analysis

1.8 match 52 stars 10.02 score 173 scripts 3 dependents

jdonaldson

tsne:T-Distributed Stochastic Neighbor Embedding for R (t-SNE)

A "pure R" implementation of the t-SNE algorithm.

Maintained by Justin Donaldson. Last updated 6 years ago.

1.9 match 58 stars 9.35 score 656 scripts 13 dependents

fatore

mp:Multidimensional Projection Techniques

Multidimensional projection techniques are used to create two dimensional representations of multidimensional data sets.

Maintained by Francisco M. Fatore. Last updated 7 years ago.

openblas cpp

4.2 match 5 stars 4.15 score 14 scripts

marekslenker

MorphoTools2:Multivariate Morphometric Analysis

Tools for multivariate analyses of morphological data, wrapped in one package, to make the workflow convenient and fast. Statistical and graphical tools provide a comprehensive framework for checking and manipulating input data, statistical analyses, and visualization of results. Several methods are provided for the analysis of raw data, to make the dataset ready for downstream analyses. Integrated statistical methods include hierarchical classification, principal component analysis, principal coordinates analysis, non-metric multidimensional scaling, and multiple discriminant analyses: canonical, stepwise, and classificatory (linear, quadratic, and the non-parametric k nearest neighbours). The philosophy of the package is described in Šlenker et al. 2022.

Maintained by Marek Šlenker. Last updated 6 months ago.

3.5 match 7 stars 5.02 score 9 scripts

computationalstylistics

stylo:Stylometric Multivariate Analyses

Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.

Maintained by Maciej Eder. Last updated 2 months ago.

2.0 match 187 stars 8.58 score 462 scripts

sergioventurini

dmbc:Model Based Clustering of Binary Dissimilarity Measurements

Functions for fitting a Bayesian model for grouping binary dissimilarity matrices in homogeneous clusters. Currently, it includes methods only for binary data (<doi:10.18637/jss.v100.i16>).

Maintained by Sergio Venturini. Last updated 6 months ago.

openblas cpp openmp

5.1 match 2 stars 3.30 score 4 scripts

sndmrc

BasketballAnalyzeR:Analysis and Visualization of Basketball Data

Contains data and code to accompany the book P. Zuccolotto and M. Manisera (2020) Basketball Data Science. Applications with R. CRC Press. ISBN 9781138600799.

Maintained by Marco Sandri. Last updated 2 years ago.

basketball-stats data-analysis data-science

3.5 match 35 stars 4.83 score 39 scripts

bioc

MicrobiotaProcess:A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework

MicrobiotaProcess is an R package for analysis, visualization and biomarker discovery of microbial datasets. It introduces MPSE class, this make it more interoperable with the existing computing ecosystem. Moreover, it introduces a tidy microbiome data structure paradigm and analysis grammar. It provides a wide variety of microbiome data analysis procedures under the unified and common framework (tidy-like framework).

Maintained by Shuangbin Xu. Last updated 5 months ago.

visualization microbiome software multiplecomparison featureextraction microbiome-analysis microbiome-data

1.7 match 183 stars 9.70 score 126 scripts 1 dependents

pridiltal

clap:Detecting Class Overlapping Regions in Multidimensional Data

The issue of overlapping regions in multidimensional data arises when different classes or clusters share similar feature representations, making it challenging to delineate distinct boundaries between them accurately. This package provides methods for detecting and visualizing these overlapping regions using partitional clustering techniques based on nearest neighbor distances.

Maintained by Priyanga Dilini Talagala. Last updated 8 months ago.

5.1 match 1 stars 3.18 score 2 scripts

forsbergpyschometrics

D3mirt:Descriptive 3D Multidimensional Item Response Theory Modelling

For identifying, estimating, and plotting descriptive multidimensional item response theory models, restricted to 3D and dichotomous or polytomous data that fit the two-parameter logistic model or the graded response model. The method is foremost explorative and centered around the plot function that exposes item characteristics and constructs, represented by vector arrows, located in a three-dimensional interactive latent space. The results can be useful for item-level analysis as well as test development.

Maintained by Erik Forsberg. Last updated 23 days ago.

3.4 match 4.74 score 4 scripts

egenn

rtemis:Machine Learning and Visualization

Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.

Maintained by E.D. Gennatas. Last updated 1 months ago.

data-science data-visualization machine-learning machine-learning-library visualization

2.3 match 145 stars 7.09 score 50 scripts 2 dependents

cran

MDSMap:High Density Genetic Linkage Mapping using Multidimensional Scaling

Estimate genetic linkage maps for markers on a single chromosome (or in a single linkage group) from pairwise recombination fractions or intermarker distances using weighted metric multidimensional scaling. The methods are suitable for autotetraploid as well as diploid populations. Options for assessing the fit to a known map are also provided. Methods are discussed in detail in Preedy and Hackett (2016) <doi:10.1007/s00122-016-2761-8>.

Maintained by Bram Boskamp. Last updated 7 years ago.

5.0 match 3.08 score 1 dependents

bioc

systemPipeTools:Tools for data visualization

systemPipeTools package extends the widely used systemPipeR (SPR) workflow environment with an enhanced toolkit for data visualization, including utilities to automate the data visualizaton for analysis of differentially expressed genes (DEGs). systemPipeTools provides data transformation and data exploration functions via scatterplots, hierarchical clustering heatMaps, principal component analysis, multidimensional scaling, generalized principal components, t-Distributed Stochastic Neighbor embedding (t-SNE), and MA and volcano plots. All these utilities can be integrated with the modular design of the systemPipeR environment that allows users to easily substitute any of these features and/or custom with alternatives.

Maintained by Daniela Cassol. Last updated 5 months ago.

infrastructure dataimport sequencing qualitycontrol reportwriting experimentaldesign clustering differentialexpression multidimensionalscaling principalcomponent

3.8 match 4.00 score 4 scripts

helske

seqHMM:Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

Designed for fitting hidden (latent) Markov models and mixture hidden Markov models for social sequence data and other categorical time series. Also some more restricted versions of these type of models are available: Markov models, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and hidden Markov models. Models are estimated using maximum likelihood via the EM algorithm and/or direct numerical maximization with analytical gradients. All main algorithms are written in C++ with support for parallel computation. Documentation is available via several vignettes in this page, and the paper by Helske and Helske (2019, <doi:10.18637/jss.v088.i03>).

Maintained by Jouni Helske. Last updated 2 years ago.

categorical-data em-algorithm hidden-markov-models hmm mixture-markov-models time-series openblas cpp openmp

1.8 match 97 stars 8.51 score 92 scripts 1 dependents

mplex

multiplex:Algebraic Tools for the Analysis of Multiple Social Networks

Algebraic procedures for analyses of multiple social networks are delivered with this package as described in Ostoic (2020) <DOI:10.18637/jss.v092.i11>. 'multiplex' makes possible, among other things, to create and manipulate multiplex, multimode, and multilevel network data with different formats. Effective ways are available to treat multiple networks with routines that combine algebraic systems like the partially ordered semigroup with decomposition procedures or semiring structures with the relational bundles occurring in different types of multivariate networks. 'multiplex' provides also an algebraic approach for affiliation networks through Galois derivations between families of the pairs of subsets in the two domains of the network with visualization options.

Maintained by Antonio Rivero Ostoic. Last updated 2 months ago.

algebra network-analysis semigroup semiring

1.9 match 23 stars 8.12 score 69 scripts 2 dependents

pvermees

provenance:Statistical Toolbox for Sedimentary Provenance Analysis

Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper, Wasserstein-2 or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances,and count data with the chi-square distance. Varietal data can either be converted to one or more distributional datasets, or directly compared using the multivariate Wasserstein distance. Also included are tools to plot compositional and count data on ternary diagrams and point-counting data on radial plots, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.

Maintained by Pieter Vermeesch. Last updated 2 months ago.

2.8 match 14 stars 5.52 score 79 scripts 1 dependents

jsilve24

fido:Bayesian Multinomial Logistic Normal Regression

Provides methods for fitting and inspection of Bayesian Multinomial Logistic Normal Models using MAP estimation and Laplace Approximation as developed in Silverman et. Al. (2022) <https://www.jmlr.org/papers/v23/19-882.html>. Key functionality is implemented in C++ for scalability. 'fido' replaces the previous package 'stray'.

Maintained by Justin Silverman. Last updated 18 days ago.

cpp openmp

1.8 match 20 stars 8.31 score 103 scripts

hfgolino

EGAnet:Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics

Implements the Exploratory Graph Analysis (EGA) framework for dimensionality and psychometric assessment. EGA estimates the number of dimensions in psychological data using network estimation methods and community detection algorithms. A bootstrap method is provided to assess the stability of dimensions and items. Fit is evaluated using the Entropy Fit family of indices. Unique Variable Analysis evaluates the extent to which items are locally dependent (or redundant). Network loadings provide similar information to factor loadings and can be used to compute network scores. A bootstrap and permutation approach are available to assess configural and metric invariance. Hierarchical structures can be detected using Hierarchical EGA. Time series and intensive longitudinal data can be analyzed using Dynamic EGA, supporting individual, group, and population level assessments.

Maintained by Hudson Golino. Last updated 9 days ago.

1.9 match 47 stars 7.80 score 61 scripts 1 dependents

r-forge

smacofx:Flexible Multidimensional Scaling and 'smacof' Extensions

Flexible multidimensional scaling (MDS) methods and extensions to the package 'smacof'. This package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different flexible MDS models. These are: Torgerson scaling (Torgerson, 1958, ISBN:978-0471879459) with powers, Sammon mapping (Sammon, 1969, <doi:10.1109/T-C.1969.222678>) with ratio and interval optimal scaling, Multiscale MDS (Ramsay, 1977, <doi:10.1007/BF02294052>) with ratio and interval optimal scaling, s-stress MDS (ALSCAL; Takane, Young & De Leeuw, 1977, <doi:10.1007/BF02293745>) with ratio and interval optimal scaling, elastic scaling (McGee, 1966, <doi:10.1111/j.2044-8317.1966.tb00367.x>) with ratio and interval optimal scaling, r-stress MDS (De Leeuw, Groenen & Mair, 2016, <https://rpubs.com/deleeuw/142619>) with ratio, interval, splines and nonmetric optimal scaling, power-stress MDS (POST-MDS; Buja & Swayne, 2002 <doi:10.1007/s00357-001-0031-0>) with ratio and interval optimal scaling, restricted power-stress (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>) with ratio and interval optimal scaling, approximate power-stress with ratio optimal scaling (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>), Box-Cox MDS (Chen & Buja, 2013, <https://jmlr.org/papers/v14/chen13a.html>), local MDS (Chen & Buja, 2009, <doi:10.1198/jasa.2009.0111>), curvilinear component analysis (Demartines & Herault, 1997, <doi:10.1109/72.554199>), curvilinear distance analysis (Lee, Lendasse & Verleysen, 2004, <doi:10.1016/j.neucom.2004.01.007>), nonlinear MDS with optimal dissimilarity powers functions (De Leeuw, 2024, <https://github.com/deleeuw/smacofManual/blob/main/smacofPO/smacofPO.pdf>), sparsified (power) MDS and sparsified multidimensional (power) distance analysis (Rusch, 2024, <doi:10.57938/355bf835-ddb7-42f4-8b85-129799fc240e>). Some functions are suitably flexible to allow any other sensible combination of explicit power transformations for weights, distances and input proximities with implicit ratio, interval, splines or nonmetric optimal scaling of the input proximities. Most functions use a Majorization-Minimization algorithm. Currently the methods are only available for one-mode data (symmetric dissimilarity matrices).

Maintained by Thomas Rusch. Last updated 2 months ago.

3.8 match 1 stars 3.89 score 2 dependents

weiserc

mvQuad:Methods for Multivariate Quadrature

Provides methods to construct multivariate grids, which can be used for multivariate quadrature. This grids can be based on different quadrature rules like Newton-Cotes formulas (trapezoidal-, Simpson's- rule, ...) or Gauss quadrature (Gauss-Hermite, Gauss-Legendre, ...). For the construction of the multidimensional grid the product-rule or the combination- technique can be applied.

Maintained by Constantin Weiser. Last updated 9 years ago.

2.3 match 3 stars 6.15 score 45 scripts 7 dependents

whateverliu

FLSSS:Mining Rigs for Problems in the Subset Sum Family

Specialized solvers for combinatorial optimization problems in the Subset Sum family. The solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value multisets with predefined subset sum errors, (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The multi-threaded framework for the latter offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Historical updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) option of mapping floating-point instance to compressed 64-bit integer instance with user-controlled precision loss, which could yield substantial speedup due to the dimension reduction and efficient compressed integer arithmetic via bit-manipulations; (e) distributed computing infrastructure for multidimensional subset sum; (f) arbitrary-precision zero-margin-of-error multidimensional Subset Sum accelerated by a simplified Bloom filter. The package contains a copy of xxHash from <https://github.com/Cyan4973/xxHash>. Package vignette (<doi:10.48550/arXiv.1612.04484>) detailed a few historical updates. Functions prefixed with 'aux' (auxiliary) are independent implementations of published algorithms for solving optimization problems less relevant to Subset Sum.

Maintained by Charlie Wusuo Liu. Last updated 2 months ago.

gmp cpp

7.9 match 1 stars 1.78 score 20 scripts

mschubert

narray:Subset- And Name-Aware Array Utility Functions

Stacking arrays according to dimension names, subset-aware splitting and mapping of functions, intersecting along arbitrary dimensions, converting to and from data.frames, and many other helper functions.

Maintained by Michael Schubert. Last updated 2 months ago.

array utility cpp

2.0 match 27 stars 6.91 score 10 scripts 10 dependents

ryansunwork

csmGmm:Conditionally Symmetric Multidimensional Gaussian Mixture Model

Implements the conditionally symmetric multidimensional Gaussian mixture model (csmGmm) for large-scale testing of composite null hypotheses in genetic association applications such as mediation analysis, pleiotropy analysis, and replication analysis. In such analyses, we typically have J sets of K test statistics where K is a small number (e.g. 2 or 3) and J is large (e.g. 1 million). For each one of the J sets, we want to know if we can reject all K individual nulls. Please see the vignette for a quickstart guide. The paper describing these methods is "Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric Multidimensional Gaussian Mixtures in Genome-Wide Studies" by Sun R, McCaw Z, & Lin X (2024, <doi:10.1080/01621459.2024.2422124>). The paper is accepted and published online (but not yet in print) in the Journal of the American Statistical Association as of Dec 1 2024.

Maintained by Ryan Sun. Last updated 3 months ago.

3.7 match 3.73 score 108 scripts

temp20250212

MultiTraits:Analyzing and Visualizing Multidimensional Plant Traits

Implements analytical methods for multidimensional plant traits, including Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. Provides functions for data analysis, visualization, and network metrics calculation. Methods are based on Grime (1974) <doi:10.1038/250026a0>, Pierce et al. (2017) <doi:10.1111/1365-2435.12882>, Westoby (1998) <doi:10.1023/A:1004327224729>, Yang et al. (2022) <doi:10.1016/j.foreco.2022.120540>, Winemiller et al. (2015) <doi:10.1111/ele.12462>, He et al. (2020) <doi:10.1016/j.tree.2020.06.003>.

Maintained by Anonymous Author. Last updated 23 days ago.

3.5 match 3.90 score 16 scripts

busingfmta

fmdu:(Restricted) [external] Multidimensional Unfolding

Functions for performing (external) multidimensional unfolding. Restrictions (fixed coordinates or model restrictions) are available for both row and column coordinates in all combinations.

Maintained by Frank Busing. Last updated 3 months ago.

9.2 match 1.48 score 1 dependents

lcbc-uio

questionnaires:Package with functions to calculate components and sums for LCBC questionnaires

Creates summaries and factorials of answers to questionnaires.

Maintained by Athanasia Mo Mowinckel. Last updated 2 years ago.

2.9 match 3 stars 4.63 score 13 scripts

juliuspfadt

Bayesrel:Bayesian Reliability Estimation

Functionality for reliability estimates. For 'unidimensional' tests: Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower bound and coefficient omega_u ('unidimensional') in a Bayesian and a frequentist version. For multidimensional tests: omega_t (total) and omega_h (hierarchical). The results include confidence and credible intervals, the probability of a coefficient being larger than a cutoff, and a check for the factor models, necessary for the omega coefficients. The method for the Bayesian 'unidimensional' estimates, except for omega_u, is sampling from the posterior inverse 'Wishart' for the covariance matrix based measures (see 'Murphy', 2007, <https://groups.seas.harvard.edu/courses/cs281/papers/murphy-2007.pdf>. The Bayesian omegas (u, t, and h) are obtained by 'Gibbs' sampling from the conditional posterior distributions of (1) the single factor model, (2) the second-order factor model, (3) the bi-factor model, (4) the correlated factor model ('Lee', 2007, <https://onlinelibrary.wiley.com/doi/book/10.1002/9780470024737>).

Maintained by Julius M. Pfadt. Last updated 11 months ago.

openblas cpp

3.9 match 3.48 score 9 scripts 1 dependents

raim

segmenTier:Similarity-Based Segmentation of Multidimensional Signals

A dynamic programming solution to segmentation based on maximization of arbitrary similarity measures within segments. The general idea, theory and this implementation are described in Machne, Murray & Stadler (2017) <doi:10.1038/s41598-017-12401-8>. In addition to the core algorithm, the package provides time-series processing and clustering functions as described in the publication. These are generally applicable where a `k-means` clustering yields meaningful results, and have been specifically developed for clustering of the Discrete Fourier Transform of periodic gene expression data (`circadian' or `yeast metabolic oscillations'). This clustering approach is outlined in the supplemental material of Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>), and here is used as a basis of segment similarity measures. Notably, the time-series processing and clustering functions can also be used as stand-alone tools, independent of segmentation, e.g., for transcriptome data already mapped to genes.

Maintained by Rainer Machne. Last updated 4 years ago.

cpp

3.0 match 3 stars 4.48 score 8 scripts

bioc

Rcpi:Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

A molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.

Maintained by Nan Xiao. Last updated 5 months ago.

software dataimport datarepresentation featureextraction cheminformatics biomedicalinformatics proteomics go systemsbiology bioconductor bioinformatics drug-discovery feature-extraction fingerprint molecular-descriptors protein-sequences

1.7 match 37 stars 7.81 score 29 scripts

xytangtang

ProcData:Process Data Analysis

Provides tools for exploratory process data analysis. Process data refers to the data describing participants' problem-solving processes in computer-based assessments. It is often recorded in computer log files. This package provides functions to read, process, and write process data. It also implements two feature extraction methods to compress the information stored in process data into standard numerical vectors. This package also provides recurrent neural network based models that relate response processes with other binary or scale variables of interest. The functions that involve training and evaluating neural networks are wrappers of functions in 'keras'.

Maintained by Xueying Tang. Last updated 4 years ago.

cpp

3.6 match 10 stars 3.70 score 2 scripts

mmollina

mappoly:Genetic Linkage Maps in Autopolyploids

Construction of genetic maps in autopolyploid full-sib populations. Uses pairwise recombination fraction estimation as the first source of information to sequentially position allelic variants in specific homologous chromosomes. For situations where pairwise analysis has limited power, the algorithm relies on the multilocus likelihood obtained through a hidden Markov model (HMM). For more detail, please see Mollinari and Garcia (2019) <doi:10.1534/g3.119.400378> and Mollinari et al. (2020) <doi:10.1534/g3.119.400620>.

Maintained by Marcelo Mollinari. Last updated 11 days ago.

polyploid polyploid-genetic-mapping polyploidy cpp

1.8 match 27 stars 7.56 score 111 scripts 1 dependents

jakub-jedrusiak

mtscr:Multidimensional Top Scoring for Creativity Research

Implementation of Multidimensional Top Scoring method for creativity assessment proposed in Boris Forthmann, Maciej Karwowski, Roger E. Beaty (2023) <doi:10.1037/aca0000571>.

Maintained by Jakub Jędrusiak. Last updated 25 days ago.

creativity psychology psychometrics

3.5 match 3.70 score 1 scripts

jolars

qualpalr:Automatic Generation of Qualitative Color Palettes

Automatic generation of maximally distinct qualitative color palettes, optionally tailored to color deficiency. A list of colors or a subspace of a color space is used as input and then projected to the DIN99d color space, where colors that are maximally distinct are chosen algorithmically.

Maintained by Johan Larsson. Last updated 6 months ago.

color visualization cpp

1.8 match 23 stars 7.45 score 162 scripts 1 dependents

pachoning

bigmds:Multidimensional Scaling for Big Data

MDS is a statistic tool for reduction of dimensionality, using as input a distance matrix of dimensions n × n. When n is large, classical algorithms suffer from computational problems and MDS configuration can not be obtained. With this package, we address these problems by means of six algorithms, being two of them original proposals: - Landmark MDS proposed by De Silva V. and JB. Tenenbaum (2004). - Interpolation MDS proposed by Delicado P. and C. Pachón-García (2021) <arXiv:2007.11919> (original proposal). - Reduced MDS proposed by Paradis E (2018). - Pivot MDS proposed by Brandes U. and C. Pich (2007) - Divide-and-conquer MDS proposed by Delicado P. and C. Pachón-García (2021) <arXiv:2007.11919> (original proposal). - Fast MDS, proposed by Yang, T., J. Liu, L. McMillan and W. Wang (2006).

Maintained by Cristian Pachón García. Last updated 1 years ago.

3.1 match 17 stars 4.08 score 14 scripts

cran

SparseGrid:Sparse grid integration in R

SparseGrid is a package to create sparse grids for numerical integration, based on code from www.sparse-grids.de

Maintained by Jelmer Ypma. Last updated 13 years ago.

3.4 match 3.66 score 8 dependents

thomasp85

densityClust:Clustering by Fast Search and Find of Density Peaks

An improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100,000 samples) very efficiently. It was initially implemented by Thomas Lin Pedersen, with inputs from Sean Hughes and later improved by Xiaojie Qiu to handle large datasets with kNNs.

Maintained by Thomas Lin Pedersen. Last updated 1 years ago.

cpp

1.7 match 153 stars 7.14 score 75 scripts

dvrbts

labdsv:Ordination and Multivariate Analysis for Ecology

A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.

Maintained by David W. Roberts. Last updated 2 years ago.

fortran

2.0 match 3 stars 6.08 score 452 scripts 13 dependents

pmair78

eRm:Extended Rasch Modeling

Fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen's LR-test, item-specific Wald test, Martin-Loef-Test, nonparametric Monte-Carlo Tests, itemfit and personfit statistics including infit and outfit measures, ICC and other plots, automated stepwise item elimination, simulation module for various binary data matrices.

Maintained by Patrick Mair. Last updated 1 years ago.

fortran

1.9 match 4 stars 6.42 score 182 scripts 5 dependents

a-dudek-ue

symbolicDA:Analysis of Symbolic Data

Symbolic data analysis methods: importing/exporting data from ASSO XML Files, distance calculation for symbolic data (Ichino-Yaguchi, de Carvalho measure), zoom star plot, 3d interval plot, multidimensional scaling for symbolic interval data, dynamic clustering based on distance matrix, HINoV method for symbolic data, Ichino's feature selection method, principal component analysis for symbolic interval data, decision trees for symbolic data based on optimal split with bagging, boosting and random forest approach (+visualization), kernel discriminant analysis for symbolic data, Kohonen's self-organizing maps for symbolic data, replication and profiling, artificial symbolic data generation. (Milligan, G.W., Cooper, M.C. (1985) <doi:10.1007/BF02294245>, Breiman, L. (1996), <doi:10.1007/BF00058655>, Hubert, L., Arabie, P. (1985), <doi:10.1007%2FBF01908075>, Ichino, M., & Yaguchi, H. (1994), <doi:10.1109/21.286391>, Rand, W.M. (1971) <doi:10.1080/01621459.1971.10482356>, Calinski, T., Harabasz, J. (1974) <doi:10.1080/03610927408827101>, Breckenridge, J.N. (2000) <doi:10.1207/S15327906MBR3502_5>, Groenen, P.J.F, Winsberg, S., Rodriguez, O., Diday, E. (2006) <doi:10.1016/j.csda.2006.04.003>, Walesiak, M., Dudek, A. (2008) <doi:10.1007/978-3-540-78246-9_11>, Dudek, A. (2007), <doi:10.1007/978-3-540-70981-7_4>).

Maintained by Andrzej Dudek. Last updated 2 years ago.

5.6 match 2.08 score 40 scripts 1 dependents

biooss

sensitivity:Global Sensitivity Analysis of Model Outputs and Importance Measures

A collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.

Maintained by Bertrand Iooss. Last updated 7 months ago.

cpp

1.7 match 17 stars 6.74 score 472 scripts 8 dependents

rikoke

fbst:The Full Bayesian Evidence Test, Full Bayesian Significance Test and the e-Value

Provides access to a range of functions for computing and visualizing the Full Bayesian Significance Test (FBST) and the e-value for testing a sharp hypothesis against its alternative, and the Full Bayesian Evidence Test (FBET) and the (generalized) Bayesian evidence value for testing a composite (or interval) hypothesis against its alternative. The methods are widely applicable as long as a posterior MCMC sample is available.

Maintained by Riko Kelter. Last updated 1 years ago.

3.9 match 1 stars 2.95 score 6 scripts 1 dependents

dhaine

episensr:Basic Sensitivity Analysis of Epidemiological Results

Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", ('Springer', 2021).

Maintained by Denis Haine. Last updated 1 years ago.

bias epidemiology sensitivity-analysis statistics

1.8 match 13 stars 6.48 score 39 scripts 1 dependents

bioc

aroma.light:Light-Weight Methods for Normalization and Visualization of Microarray Data using Only Basic R Data Types

Methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Maintained by Henrik Bengtsson. Last updated 5 months ago.

infrastructure microarray onechannel twochannel multichannel visualization preprocessing bioconductor

1.8 match 1 stars 6.43 score 26 scripts 20 dependents

brandmaier

pdc:Permutation Distribution Clustering

Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.

Maintained by Andreas M. Brandmaier. Last updated 2 years ago.

2.0 match 6 stars 5.61 score 25 scripts 9 dependents

bioc

GloScope:Population-level Representation on scRNA-Seq data

This package aims at representing and summarizing the entire single-cell profile of a sample. It allows researchers to perform important bioinformatic analyses at the sample-level such as visualization and quality control. The main functions Estimate sample distribution and calculate statistical divergence among samples, and visualize the distance matrix through MDS plots.

Maintained by William Torous. Last updated 5 months ago.

datarepresentation qualitycontrol rnaseq sequencing software singlecell

1.8 match 3 stars 6.05 score 84 scripts

mthrun

ProjectionBasedClustering:Projection Based Clustering

A clustering approach applicable to every projection method is proposed here. The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on Thrun and Ultsch, "Using Projection based Clustering to Find Distance and Density based Clusters in High-Dimensional Data" <DOI:10.1007/s00357-020-09373-2>. Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.

Maintained by Michael Thrun. Last updated 3 years ago.

cpp

2.0 match 7 stars 5.33 score 34 scripts 3 dependents

yoctozepto

MDFS:MultiDimensional Feature Selection

Functions for MultiDimensional Feature Selection (MDFS): calculating multidimensional information gains, scoring variables, finding important variables, plotting selection results. This package includes an optional CUDA implementation that speeds up information gain calculation using NVIDIA GPGPUs. R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.

Maintained by Radosław Piliszek. Last updated 3 months ago.

cpp openmp

4.1 match 2.56 score 24 scripts 1 dependents

siacus

cem:Coarsened Exact Matching

Implementation of the Coarsened Exact Matching algorithm discussed along with its properties in Iacus, King, Porro (2011) <DOI:10.1198/jasa.2011.tm09599>; Iacus, King, Porro (2012) <DOI:10.1093/pan/mpr013> and Iacus, King, Porro (2019) <DOI:10.1017/pan.2018.29>.

Maintained by Stefano M. Iacus. Last updated 3 years ago.

1.8 match 2 stars 5.76 score 239 scripts 1 dependents

orenbenkiki

chameleon:Automatic Colors for Multi-Dimensional Data

Assign distinct colors to arbitrary multi-dimensional data, considering its structure.

Maintained by Oren Ben-Kiki. Last updated 2 years ago.

3.3 match 3.00 score 20 scripts

glottospace

glottospace:Language Mapping and Geospatial Analysis of Linguistic and Cultural Data

Streamlined workflows for geolinguistic analysis, including: accessing global linguistic and cultural databases, data import, data entry, data cleaning, data exploration, mapping, visualization and export.

Maintained by Rui Dong. Last updated 3 months ago.

1.8 match 23 stars 5.54 score 6 scripts

faiarte

MPI:Computation of Multidimensional Poverty Index (MPI)

Computing package for Multidimensional Poverty Index (MPI) using Alkire-Foster method. Given N individuals, each person has D indicators of deprivation, the package compute MPI value to represent the degree of poverty in a population. The inputs are 1) an N by D matrix, which has the element (i,j) represents whether an individual i is deprived in an indicator j (1 is deprived and 0 is not deprived), and 2) the deprivation threshold. The main output is the MPI value, which has the range between zero and one. MPI value is approaching one if almost all people are deprived in all indicators, and it is approaching zero if almost no people are deprived in any indicator. Please see Alkire S., Chatterjee, M., Conconi, A., Seth, S. and Ana Vaz (2014) <doi:10.35648/20.500.12413/11781/ii039> for The Alkire-Foster methodology.

Maintained by Kittiya Kukiattikun. Last updated 3 years ago.

3.5 match 2.81 score 13 scripts

bioc

broadSeq:broadSeq : for streamlined exploration of RNA-seq data

This package helps user to do easily RNA-seq data analysis with multiple methods (usually which needs many different input formats). Here the user will provid the expression data as a SummarizedExperiment object and will get results from different methods. It will help user to quickly evaluate different methods.

Maintained by Rishi Das Roy. Last updated 5 months ago.

geneexpression differentialexpression rnaseq transcriptomics sequencing coverage genesetenrichment go

2.0 match 2 stars 4.90 score 7 scripts

bioc

DAMEfinder:Finds DAMEs - Differential Allelicly MEthylated regions

'DAMEfinder' offers functionality for taking methtuple or bismark outputs to calculate ASM scores and compute DAMEs. It also offers nice visualization of methyl-circle plots.

Maintained by Stephany Orjuela. Last updated 5 months ago.

dnamethylation differentialmethylation coverage

1.7 match 10 stars 5.70 score 9 scripts

cran

startR:Automatically Retrieve Multidimensional Distributed Data Sets

Tool to automatically fetch, transform and arrange subsets of multi- dimensional data sets (collections of files) stored in local and/or remote file systems or servers, using multicore capabilities where possible. The tool provides an interface to perceive a collection of data sets as a single large multidimensional data array, and enables the user to request for automatic retrieval, processing and arrangement of subsets of the large array. Wrapper functions to add support for custom file formats can be plugged in/out, making the tool suitable for any research field where large multidimensional data sets are involved.

Maintained by Victoria Agudetse. Last updated 6 months ago.

5.4 match 1.78 score 2 dependents

albertoarcagni

parsec:Partial Orders in Socio-Economics

Implements tools for the analysis of partially ordered data, with a particular focus on the evaluation of multidimensional systems of indicators and on the analysis of poverty. References, Fattore M. (2016) <doi:10.1007/s11205-015-1059-6> Fattore M., Arcagni A. (2016) <doi:10.1007/s11205-016-1501-4> Arcagni A. (2017) <doi:10.1007/978-3-319-45421-4_19>.

Maintained by Alberto Arcagni. Last updated 2 years ago.

4.3 match 1 stars 2.21 score 54 scripts 1 dependents

cran

CSTools:Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales

Exploits dynamical seasonal forecasts in order to provide information relevant to stakeholders at the seasonal timescale. The package contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. This package was developed in the context of the 'ERA4CS' project 'MEDSCOPE' and the 'H2020 S2S4E' project and includes contributions from 'ArticXchange' project founded by 'EU-PolarNet 2'. 'Pérez-Zanón et al. (2022) <doi:10.5194/gmd-15-6115-2022>'. 'Doblas-Reyes et al. (2005) <doi:10.1111/j.1600-0870.2005.00104.x>'. 'Mishra et al. (2018) <doi:10.1007/s00382-018-4404-z>'. 'Sanchez-Garcia et al. (2019) <doi:10.5194/asr-16-165-2019>'. 'Straus et al. (2007) <doi:10.1175/JCLI4070.1>'. 'Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>'. 'Torralba et al. (2017) <doi:10.1175/JAMC-D-16-0204.1>'. 'D'Onofrio et al. (2014) <doi:10.1175/JHM-D-13-096.1>'. 'Verfaillie et al. (2017) <doi:10.5194/gmd-10-4257-2017>'. 'Van Schaeybroeck et al. (2019) <doi:10.1016/B978-0-12-812372-0.00010-8>'. 'Yiou et al. (2013) <doi:10.1007/s00382-012-1626-3>'.

Maintained by Victoria Agudetse. Last updated 1 years ago.

fortran

1.7 match 2 stars 5.32 score 62 scripts 1 dependents

h56cho

forestRK:Implements the Forest-R.K. Algorithm for Classification Problems

Provides functions that calculates common types of splitting criteria used in random forests for classification problems, as well as functions that make predictions based on a single tree or a Forest-R.K. model; the package also provides functions to generate importance plot for a Forest-R.K. model, as well as the 2D multidimensional-scaling plot of data points that are colour coded by their predicted class types by the Forest-R.K. model. This package is based on: Bernard, S., Heutte, L., Adam, S., (2008, ISBN:978-3-540-85983-3) "Forest-R.K.: A New Random Forest Induction Method", Fourth International Conference on Intelligent Computing, September 2008, Shanghai, China, pp.430-437.

Maintained by Hyunjin Cho. Last updated 6 years ago.

2.1 match 4.24 score 35 scripts

cran

stpm:Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

Utilities to estimate parameters of the models with survival functions induced by stochastic covariates. Miscellaneous functions for data preparation and simulation are also provided. For more information, see: (i)"Stochastic model for analysis of longitudinal data on aging and mortality" by Yashin A. et al. (2007), Mathematical Biosciences, 208(2), 538-551, <DOI:10.1016/j.mbs.2006.11.006>; (ii) "Health decline, aging and mortality: how are they related?" by Yashin A. et al. (2007), Biogerontology 8(3), 291(302), <DOI:10.1007/s10522-006-9073-3>.

Maintained by Ilya Y. Zhbannikov. Last updated 3 years ago.

openblas cpp openmp

3.3 match 2.70 score

mi2-warsaw

sejmRP:An Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office

Set of functions that access information about deputies and votings in Polish diet from webpage <http://www.sejm.gov.pl>. The package was developed as a result of an internship in MI2 Group - <http://mi2.mini.pw.edu.pl>, Faculty of Mathematics and Information Science, Warsaw University of Technology.

Maintained by Piotr Smuda. Last updated 8 years ago.

1.7 match 21 stars 5.04 score 35 scripts

wanchanglin

mt:Metabolomics Data Analysis Toolbox

Functions for metabolomics data analysis: data preprocessing, orthogonal signal correction, PCA analysis, PCA-DA analysis, PLS-DA analysis, classification, feature selection, correlation analysis, data visualisation and re-sampling strategies.

Maintained by Wanchang Lin. Last updated 1 years ago.

1.9 match 3 stars 4.57 score 50 scripts

yannabraham

hilbertSimilarity:Hilbert Similarity Index for High Dimensional Data

Quantifying similarity between high-dimensional single cell samples is challenging, and usually requires some simplifying hypothesis to be made. By transforming the high dimensional space into a high dimensional grid, the number of cells in each sub-space of the grid is characteristic of a given sample. Using a Hilbert curve each sample can be visualized as a simple density plot, and the distance between samples can be calculated from the distribution of cells using the Jensen-Shannon distance. Bins that correspond to significant differences between samples can identified using a simple bootstrap procedure.

Maintained by Yann Abraham. Last updated 5 years ago.

cpp

1.8 match 5 stars 4.74 score 11 scripts

lea-urpa

focusedMDS:Focused, Interactive Multidimensional Scaling

Takes a distance matrix and plots it as an interactive graph. One point is focused at the center of the graph, around which all other points are plotted in their exact distances as given in the distance matrix. All other non-focus points are plotted as best as possible in relation to one another. Double click on any point to choose a new focus point, and hover over points to see their ID labels. If color label categories are given, hover over colors in the legend to highlight only those points and click on colors to highlight multiple groups. For more information on the rationale and mathematical background, as well as an interactive introduction, see <https://lea-urpa.github.io/focusedMDS.html>.

Maintained by Lea Urpa. Last updated 8 years ago.

5.0 match 1.70 score 7 scripts

jasenfinch

pdi:Phenotypic Index Measures for Oak Decline Severity

Oak declines are complex disease syndromes and consist of many visual indicators that include aspects of tree size, crown condition and trunk condition. This can cause difficulty in the manual classification of symptomatic and non-symptomatic trees from what is in reality a broad spectrum of oak tree health condition. Two phenotypic oak decline indexes have been developed to quantitatively describe and differentiate oak decline syndromes in Quercus robur. This package provides a toolkit to generate these decline indexes from phenotypic descriptors using the machine learning algorithm random forest. The methodology for generating these indexes is outlined in Finch et al. (2121) <doi:10.1016/j.foreco.2021.118948>.

Maintained by Jasen Finch. Last updated 4 years ago.

decline index oak phenotyping

2.3 match 3.70 score 3 scripts

kisungyou

Riemann:Learning with Data on Riemannian Manifolds

We provide a variety of algorithms for manifold-valued data, including Fréchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.

Maintained by Kisung You. Last updated 2 years ago.

openblas cpp openmp

2.3 match 10 stars 3.70 score 8 scripts

silviadangelo

spaceNet:Latent Space Models for Multidimensional Networks

Latent space models for multivariate networks (multiplex) estimated via MCMC algorithm. See D Angelo et al. (2018) <arXiv:1803.07166> and D Angelo et al. (2018) <arXiv:1807.03874>.

Maintained by Silvia DAngelo. Last updated 6 years ago.

8.3 match 1 stars 1.00 score 6 scripts

loick-klpr

specieschrom:The Species Chromatogram

A simple method to display and characterise the multidimensional ecological niche of a species. The method also estimates the optimums and amplitudes along each niche dimension. Give also an estimation of the degree of niche overlapping between species. See Kleparski and Beaugrand (2022) <doi:10.1002/ece3.8830> for further details.

Maintained by Loick Kleparski. Last updated 2 years ago.

2.2 match 1 stars 3.70 score 3 scripts

irsn

DiceView:Methods for Visualization of Computer Experiments Design and Surrogate

View 2D/3D sections, contour plots, mesh of excursion sets for computer experiments designs, surrogates or test functions.

Maintained by Yann Richet. Last updated 3 months ago.

2.0 match 1 stars 4.06 score 33 scripts

cran

MLCIRTwithin:Latent Class Item Response Theory (LC-IRT) Models under Within-Item Multidimensionality

Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of within-item multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parametrizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version together with possibility of constraints on all model parameters.

Maintained by Francesco Bartolucci. Last updated 5 years ago.

8.1 match 1.00 score

mottensmann

GCalignR:Simple Peak Alignment for Gas-Chromatography Data

Aligns peak based on peak retention times and matches homologous peaks across samples. The underlying alignment procedure comprises three sequential steps. (1) Full alignment of samples by linear transformation of retention times to maximise similarity among homologous peaks (2) Partial alignment of peaks within a user-defined retention time window to cluster homologous peaks (3) Merging rows that are likely representing homologous substances (i.e. no sample shows peaks in both rows and the rows have similar retention time means). The algorithm is described in detail in Ottensmann et al., 2018 <doi:10.1371/journal.pone.0198311>.

Maintained by Meinolf Ottensmann. Last updated 6 months ago.

1.3 match 5 stars 6.39 score 41 scripts

cran

HMP:Hypothesis Testing and Power Calculations for Comparing Metagenomic Samples from HMP

Using Dirichlet-Multinomial distribution to provide several functions for formal hypothesis testing, power and sample size calculations for human microbiome experiments.

Maintained by Berkley Shands. Last updated 6 years ago.

1.8 match 1 stars 4.37 score 78 scripts 1 dependents

rstudio

tensorflow:R Interface to 'TensorFlow'

Interface to 'TensorFlow' <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, server, or mobile device with a single 'API'. 'TensorFlow' was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

Maintained by Tomasz Kalinowski. Last updated 16 days ago.

0.5 match 1.3k stars 15.35 score 3.2k scripts 74 dependents

simonepadoan

ExtremeRisks:Extreme Risk Measures

A set of procedures for estimating risks related to extreme events via risk measures such as Expectile, Value-at-Risk, etc. is provided. Estimation methods for univariate independent observations and temporal dependent observations are available. The methodology is extended to the case of independent multidimensional observations. The statistical inference is performed through parametric and non-parametric estimators. Inferential procedures such as confidence intervals, confidence regions and hypothesis testing are obtained by exploiting the asymptotic theory. Adapts the methodologies derived in Padoan and Stupfler (2020) <arxiv:2004.04078>, Padoan and Stupfler (2020) <arxiv:2007.08944>, Daouia et al. (2018) <doi:10.1111/rssb.12254>, Drees (2000) <doi:10.1214/aoap/1019487617>, Drees (2003) <doi:10.3150/bj/1066223272>, de Haan and Ferreira (2006) <doi:10.1007/0-387-34471-3>, de Haan et al. (2016) <doi:10.1007/s00780-015-0287-6>.

Maintained by Simone Padoan. Last updated 5 years ago.

7.7 match 1 stars 1.00 score 3 scripts

agdamsbo

stRoke:Clinical Stroke Research

A collection of tools for clinical trial data management and analysis in research and teaching. The package is mainly collected for personal use, but any use beyond that is encouraged. This package has migrated functions from 'agdamsbo/daDoctoR', and new functions has been added. Version follows months and year. See NEWS/Changelog for release notes. This package includes sampled data from the TALOS trial (Kraglund et al (2018) <doi:10.1161/STROKEAHA.117.020067>). The win_prob() function is based on work by Zou et al (2022) <doi:10.1161/STROKEAHA.121.037744>. The age_calc() function is based on work by Becker (2020) <doi:10.18637/jss.v093.i02>.

Maintained by Andreas Gammelgaard Damsbo. Last updated 5 months ago.

neuroscience stroke

1.8 match 4.18 score 7 scripts

cran

Mestim:Computes the Variance-Covariance Matrix of Multidimensional Parameters Using M-Estimation

Provides a flexible framework for estimating the variance-covariance matrix of estimated parameters. Estimation relies on unbiased estimating functions to compute the empirical sandwich variance. (i.e., M-estimation in the vein of Tsiatis et al. (2019) <doi:10.1201/9780429192692>.

Maintained by François Grolleau. Last updated 2 years ago.

2.8 match 2.70 score

njlyon0

supportR:Support Functions for Wrangling and Visualization

Suite of helper functions for data wrangling and visualization. The only theme for these functions is that they tend towards simple, short, and narrowly-scoped. These functions are built for tasks that often recur but are not large enough in scope to warrant an ecosystem of interdependent functions.

Maintained by Nicholas J Lyon. Last updated 4 months ago.

data-science

1.2 match 5 stars 6.22 score 15 scripts

hdraisma

represent:Determine How Representative Two Multidimensional Data Sets are

Compute the values of various parameters evaluating how similar two multidimensional datasets' structures are in multidimensional space, as described in: Jouan-Rimbaud, D., Massart, D. L., Saby, C. A., Puel, C. (1998), <doi:10.1016/S0169-7439(98)00005-7>. The computed parameters evaluate three properties, namely, the direction of the data sets, the variance-covariance of the data points, and the location of the data sets' centroids. The package contains workhorse function jrparams(), as well as two helper functions Mboxtest() and JRsMahaldist(), and four example data sets.

Maintained by Harmen Draisma. Last updated 1 years ago.

7.2 match 1.00 score 5 scripts

bioc

CytoMDS:Low Dimensions projection of cytometry samples

This package implements a low dimensional visualization of a set of cytometry samples, in order to visually assess the 'distances' between them. This, in turn, can greatly help the user to identify quality issues like batch effects or outlier samples, and/or check the presence of potential sample clusters that might align with the exeprimental design. The CytoMDS algorithm combines, on the one hand, the concept of Earth Mover's Distance (EMD), a.k.a. Wasserstein metric and, on the other hand, the Multi Dimensional Scaling (MDS) algorithm for the low dimensional projection. Also, the package provides some diagnostic tools for both checking the quality of the MDS projection, as well as tools to help with the interpretation of the axes of the projection.

Maintained by Philippe Hauchamps. Last updated 2 months ago.

flowcytometry qualitycontrol dimensionreduction multidimensionalscaling software visualization

1.3 match 1 stars 5.32 score 2 scripts

bioc

clst:Classification by local similarity threshold

Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons.

Maintained by Noah Hoffman. Last updated 5 months ago.

classification

1.9 match 3.78 score 10 scripts 1 dependents

yujiaomai

OmegaG:Omega-Generic: Composite Reliability of Multidimensional Measures

It is a computer tool to estimate the item-sum score's reliability (composite reliability, CR) in multidimensional scales with overlapping items. An item that measures more than one domain construct is called an overlapping item. The estimation is based on factor models allowing unlimited cross-factor loadings such as exploratory structural equation modeling (ESEM) and Bayesian structural equation modeling (BSEM). The factor models include correlated-factor models and bi-factor models. Specifically for bi-factor models, a type of hierarchical factor model, the package estimates the CR hierarchical subscale/hierarchy and CR subscale/scale total. The CR estimator 'Omega-generic' was proposed by Mai, Srivastava, and Krull (2021) <https://whova.com/embedded/subsession/enars_202103/1450751/1452993/>. The current version can only handle continuous data. Yujiao Mai contributes to the algorithms, R programming, and application example. Deo Kumar Srivastava contributes to the algorithms and the application example. Kevin R. Krull contributes to the application example. The package 'OmegaG' was sponsored by American Lebanese Syrian Associated Charities (ALSAC). However, the contents of 'OmegaG' do not necessarily represent the policy of the ALSAC.

Maintained by Yujiao Mai. Last updated 4 years ago.

6.9 match 1.00 score

winzarh

LikertMakeR:Synthesise and Correlate Likert Scale and Rating-Scale Data Based on Summary Statistics Only

Generate and correlate synthetic Likert and rating-scale data with predefined means, standard deviations, _Cronbach's Alpha_, _Factor Loading table_, and other summary statistics.

Maintained by Hume Winzar. Last updated 13 days ago.

openblas cpp

1.2 match 6 stars 5.80 score 7 scripts

cran

HDoutliers:Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers

An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers.

Maintained by Chris Fraley. Last updated 3 years ago.

3.4 match 3 stars 1.95 score 1 dependents

cran

clustering.sc.dp:Optimal Distance-Based Clustering for Multidimensional Data with Sequential Constraint

A dynamic programming algorithm for optimal clustering multidimensional data with sequential constraint. The algorithm minimizes the sum of squares of within-cluster distances. The sequential constraint allows only subsequent items of the input data to form a cluster. The sequential constraint is typically required in clustering data streams or items with time stamps such as video frames, GPS signals of a vehicle, movement data of a person, e-pen data, etc. The algorithm represents an extension of 'Ckmeans.1d.dp' to multiple dimensional spaces. Similarly to the one-dimensional case, the algorithm guarantees optimality and repeatability of clustering. Method clustering.sc.dp() can find the optimal clustering if the number of clusters is known. Otherwise, methods findwithinss.sc.dp() and backtracking.sc.dp() can be used. See Szkaliczki, T. (2016) "clustering.sc.dp: Optimal Clustering with Sequential Constraint by Using Dynamic Programming" <doi: 10.32614/RJ-2016-022> for more information.

Maintained by Tibor Szkaliczki. Last updated 2 years ago.

cpp

6.7 match 1.00 score

bioc

FISHalyseR:FISHalyseR a package for automated FISH quantification

FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.

Maintained by Karesh Arunakirinathan. Last updated 5 months ago.

cellbiology

2.0 match 3.30 score 2 scripts

bioc

MIRit:Integrate microRNA and gene expression to decipher pathway complexity

MIRit is an R package that provides several methods for investigating the relationships between miRNAs and genes in different biological conditions. In particular, MIRit allows to explore the functions of dysregulated miRNAs, and makes it possible to identify miRNA-gene regulatory axes that control biological pathways, thus enabling the users to unveil the complexity of miRNA biology. MIRit is an all-in-one framework that aims to help researchers in all the central aspects of an integrative miRNA-mRNA analyses, from differential expression analysis to network characterization.

Maintained by Jacopo Ronchi. Last updated 3 days ago.

software generegulation networkenrichment networkinference epigenetics functionalgenomics systemsbiology network pathways geneexpression differentialexpression mirna mirna-mrna-interaction mirna-seq mirnaseq-analysis cpp

1.7 match 4.00 score 2 scripts

flxzimmer

irtpwr:Power Analysis for IRT Models Using the Wald, LR, Score, and Gradient Statistics

Implementation of analytical and sampling-based power analyses for the Wald, likelihood ratio (LR), score, and gradient tests. Can be applied to item response theory (IRT) models that are fitted using marginal maximum likelihood estimation. The methods are described in our paper (Zimmer et al. (2022) <doi:10.1007/s11336-022-09883-5>).

Maintained by Felix Zimmer. Last updated 1 years ago.

1.5 match 1 stars 4.30 score 9 scripts

bioc

Damsel:Damsel: an end to end analysis of DamID

Damsel provides an end to end analysis of DamID data. Damsel takes bam files from Dam-only control and fusion samples and counts the reads matching to each GATC region. edgeR is utilised to identify regions of enrichment in the fusion relative to the control. Enriched regions are combined into peaks, and are associated with nearby genes. Damsel allows for IGV style plots to be built as the results build, inspired by ggcoverage, and using the functionality and layering ability of ggplot2. Damsel also conducts gene ontology testing with bias correction through goseq, and future versions of Damsel will also incorporate motif enrichment analysis. Overall, Damsel is the first package allowing for an end to end analysis with visual capabilities. The goal of Damsel was to bring all the analysis into one place, and allow for exploratory analysis within R.

Maintained by Caitlin Page. Last updated 5 months ago.

differentialmethylation peakdetection geneprediction genesetenrichment

1.2 match 5.34 score 20 scripts

nplatonov

ursa:Non-Interactive Spatial Tools for Raster Processing and Visualization

S3 classes and methods for manipulation with georeferenced raster data: reading/writing, processing, multi-panel visualization.

Maintained by Nikita Platonov. Last updated 11 months ago.

1.8 match 7 stars 3.54 score 5 scripts

imehlhaff

CPC:Implementation of Cluster-Polarization Coefficient

Implements cluster-polarization coefficient for measuring distributional polarization in single or multiple dimensions, as well as associated functions. Contains support for hierarchical clustering, k-means, partitioning around medoids, density-based spatial clustering with noise, and manually imposed cluster membership. Mehlhaff (forthcoming) <doi:10.1017/S0003055423001041>.

Maintained by Isaac Mehlhaff. Last updated 5 months ago.

2.0 match 3.18 score 9 scripts

bioc

ScreenR:Package to Perform High Throughput Biological Screening

ScreenR is a package suitable to perform hit identification in loss of function High Throughput Biological Screenings performed using barcoded shRNA-based libraries. ScreenR combines the computing power of software such as edgeR with the simplicity of use of the Tidyverse metapackage. ScreenR executes a pipeline able to find candidate hits from barcode counts, and integrates a wide range of visualization modes for each step of the analysis.

Maintained by Emanuel Michele Soda. Last updated 5 months ago.

software assaydomain geneexpression high-throughput-screening

2.0 match 1 stars 3.11 score 13 scripts

fherla

sarp.snowprofile.alignment:Snow Profile Alignment, Aggregation, and Clustering

Snow profiles describe the vertical (1D) stratigraphy of layered snow with different layer characteristics, such as grain type, hardness, deposition date, and many more. Hence, they represent a data format similar to multivariate time series containing categorical, ordinal, and numerical data types. Use this package to align snow profiles by matching their individual layers based on Dynamic Time Warping (DTW). The aligned profiles can then be assessed with an independent, global similarity measure that is geared towards avalanche hazard assessment. Finally, through exploiting data aggregation and clustering methods, the similarity measure provides the foundation for grouping and summarizing snow profiles according to similar hazard conditions. In particular, this package allows for averaging large numbers of snow profiles with DTW Barycenter Averaging and thereby facilitates the computation of individual layer distributions and summary statistics that are relevant for avalanche forecasting purposes. For more background information refer to Herla, Horton, Mair, and Haegeli (2021) <doi:10.5194/gmd-14-239-2021>, Herla, Mair, and Haegeli (2022) <doi:10.5194/tc-16-3149-2022>, and Horton, Herla, and Haegeli (2024) <doi:10.5194/egusphere-2024-1609>.

Maintained by Florian Herla. Last updated 7 months ago.

1.8 match 3.45 score 14 scripts

leahfeuerstahler

scaleAlign:Scale Alignment for Between-Items Multidimensional Rasch Family Models

Scale alignment is a new procedure for rescaling dimensions of between-items multidimensional Rasch family models so that dimensions scores can be compared directly (Feuerstahler & Wilson, 2019; under review) <doi:10.1111/jedm.12209>. This package includes functions for implementing delta-dimensional alignment (DDA) and logistic regression alignment (LRA) for dichotomous or polytomous data. This function also includes a wrapper for models fit using the 'TAM' package.

Maintained by Leah Feuerstahler. Last updated 5 years ago.

3.4 match 1.70 score

henrikbengtsson

sfit:Multidimensional Simplex Fitting

Methods for robustly fitting a K-dimensional simplex in M dimensions.

Maintained by Henrik Bengtsson. Last updated 2 years ago.

c cone model simplex

3.3 match 1 stars 1.70 score

adamkocsis

via:Virtual Arrays

The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.

Maintained by Adam T. Kocsis. Last updated 2 years ago.

1.8 match 3 stars 3.18 score 8 scripts

pmair78

semds:Structural Equation Multidimensional Scaling

Fits a structural equation multidimensional scaling (SEMDS) model for asymmetric and three-way input dissimilarities. It assumes that the dissimilarities are measured with errors. The latent dissimilarities are estimated as factor scores within an SEM framework while the objects are represented in a low-dimensional space as in MDS.

Maintained by Patrick Mair. Last updated 6 years ago.

5.5 match 1.00 score 7 scripts

minhyung-kang

KSD:Goodness-of-Fit Tests using Kernelized Stein Discrepancy

An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <arXiv:1602.03253>.

Maintained by Min Hyung Kang. Last updated 4 years ago.

1.8 match 3.04 score 11 scripts

cran

MVar.pt:Analise multivariada (brazilian portuguese)

Analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, biplot, scatter plot, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.

Maintained by Paulo Cesar Ossani. Last updated 4 months ago.

2.5 match 2.17 score 37 scripts

mansukoh

bayMDS:Bayesian Multidimensional Scaling and Choice of Dimension

Bayesian approach to multidimensional scaling. The package consists of implementations of the methods of Oh and Raftery (2001) <doi:10.1198/016214501753208690>.

Maintained by Man-Suk Oh. Last updated 2 years ago.

openblas cpp

5.4 match 1.00 score 1 scripts

cran

MVar:Multivariate Analysis

Multivariate analysis, having functions that perform simple correspondence analysis (CA) and multiple correspondence analysis (MCA), principal components analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), multidimensional scaling (MDS), linear (LDA) and quadratic discriminant analysis (QDA), hierarchical and non-hierarchical cluster analysis, simple and multiple linear regression, multiple factor analysis (MFA) for quantitative, qualitative, frequency (MFACT) and mixed data, biplot, scatter plot, projection pursuit (PP), grant tour method and other useful functions for the multivariate analysis.

Maintained by Paulo Cesar Ossani. Last updated 4 months ago.

2.5 match 2.09 score 31 scripts

kisungyou

TDAkit:Toolkit for Topological Data Analysis

Topological data analysis studies structure and shape of the data using topological features. We provide a variety of algorithms to learn with persistent homology of the data based on functional summaries for clustering, hypothesis testing, visualization, and others. We refer to Wasserman (2018) <doi:10.1146/annurev-statistics-031017-100045> for a statistical perspective on the topic.

Maintained by Kisung You. Last updated 4 years ago.

openblas cpp openmp

2.3 match 2 stars 2.30 score 4 scripts

cran

InDisc:Obtaining and Estimating Unidimensional and Multidimensional IRT Dual Models

Performs a unified approach for obtaining and estimating unidimensional and multidimensional Item Response Theory (IRT) Dual Models (DMs), proposed by Ferrando (2019 <doi:10.1177/0146621618817779>).

Maintained by David Navarro-Gonzalez. Last updated 4 years ago.

5.0 match 1.00 score

dan-cloney

conquestr:An R Package to Extend 'ACER ConQuest'

Extends 'ACER ConQuest' through a family of functions designed to improve graphical outputs and help with advanced analysis (e.g., differential item functioning). Allows R users to call 'ACER ConQuest' from within R and read 'ACER ConQuest' System Files (generated by the command `put` <https://conquestmanual.acer.org/s4-00.html#put>). Requires 'ACER ConQuest' version 5.40 or later. A demonstration version can be downloaded from <https://shop.acer.org/acer-conquest-5.html>.

Maintained by Dan Cloney. Last updated 26 days ago.

cpp

1.2 match 4.14 score 13 scripts

cran

FlowerMate:Reciprocity Indices for Style-Polymorphic Plants

Computes unidimensional and multidimensional Reciprocity and Inaccuracy indices. These indices are applicable to common heterostylous populations and to any other type of stylar dimorphic and trimorphic populations, such as in enantiostylous and three-dimensional heterostylous plants. Simón-Porcar, V., A. J. Muñoz-Pajares, J. Arroyo, and S. D. Johnson. (in press) "FlowerMate: multidimensional reciprocity and inaccuracy indices for style-polymorphic plant populations."

Maintained by A. J. Muñoz-Pajares Developer. Last updated 9 months ago.

2.5 match 2.00 score

dnychka

LatticeKrig:Multi-Resolution Kriging Based on Markov Random Fields

Methods for the interpolation of large spatial datasets. This package uses a basis function approach that provides a surface fitting method that can approximate standard spatial data models. Using a large number of basis functions allows for estimates that can come close to interpolating the observations (a spatial model with a small nugget variance.) Moreover, the covariance model for this method can approximate the Matern covariance family but also allows for a multi-resolution model and supports efficient computation of the profile likelihood for estimating covariance parameters. This is accomplished through compactly supported basis functions and a Markov random field model for the basis coefficients. These features lead to sparse matrices for the computations and this package makes of the R spam package for sparse linear algebra. An extension of this version over previous ones ( < 5.4 ) is the support for different geometries besides a rectangular domain. The Markov random field approach combined with a basis function representation makes the implementation of different geometries simple where only a few specific R functions need to be added with most of the computation and evaluation done by generic routines that have been tuned to be efficient. One benefit of this package's model/approach is the facility to do unconditional and conditional simulation of the field for large numbers of arbitrary points. There is also the flexibility for estimating non-stationary covariances and also the case when the observations are a linear combination (e.g. an integral) of the spatial process. Included are generic methods for prediction, standard errors for prediction, plotting of the estimated surface and conditional and unconditional simulation. See the 'LatticeKrigRPackage' GitHub repository for a vignette of this package. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research.

Maintained by Douglas Nychka. Last updated 5 months ago.

fortran

1.7 match 2.89 score 130 scripts 1 dependents

cran

cml:Conditional Manifold Learning

Finds a low-dimensional embedding of high-dimensional data, conditioning on available manifold information. The current version supports conditional MDS (based on either conditional SMACOF in Bui (2021) <arXiv:2111.13646> or closed-form solution in Bui (2022) <doi:10.1016/j.patrec.2022.11.007>) and conditional ISOMAP in Bui (2021) <arXiv:2111.13646>.

Maintained by Anh Tuan Bui. Last updated 2 years ago.

3.8 match 1.30 score

sciviews

exploreit:Exploratory Data Analysis for 'SciViews::R'

Multivariate analysis and data exploration for the 'SciViews::R' dialect.

Maintained by Philippe Grosjean. Last updated 11 months ago.

multivariate-analysis sciviews statistical-methods

1.8 match 2.70 score 4 scripts

andrefujita

statGraph:Statistical Methods for Graphs

Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the Graph Information Criterion, statistical tests to discriminate two or more populations of graphs, correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Fujita et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.

Maintained by Andre Fujita. Last updated 7 months ago.

2.0 match 2 stars 2.29 score 14 scripts

diegosasso

ontophylo:Ontology-Informed Phylogenetic Comparative Analyses

This package provides new phylogenetic tools for analyzing discrete trait data integrating bio-ontologies and phylogenetics. It expands on the previous work of Tarasov et al. (2019). The PARAMO pipeline allows to reconstruct ancestral phenomes treating groups of morphological traits as a single complex character. The pipeline incorporates knowledge from ontologies during the amalgamation of individual character stochastic maps. Here we expand the current PARAMO functionality by adding new statistical methods for inferring evolutionary phenome dynamics using non-homogeneous Poisson process (NHPP). The new functionalities include: (1) reconstruction of evolutionary rate shifts of phenomes across lineages and time; (2) reconstruction of morphospace dynamics through time; and (3) estimation of rates of phenome evolution at different levels of anatomical hierarchy (e.g., entire body or specific regions only). The package also includes user-friendly tools for visualizing evolutionary rates of different anatomical regions using PNG vector images of the organisms of interest.

Maintained by Diego S. Porto. Last updated 1 years ago.

1.7 match 2.70 score 8 scripts

alexanderrobitzsch

TAM:Test Analysis Modules

Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.

Maintained by Alexander Robitzsch. Last updated 6 months ago.

item-response-theory openblas cpp

0.5 match 16 stars 8.93 score 258 scripts 25 dependents

rubenfcasal

npsp:Nonparametric Spatial Statistics

Multidimensional nonparametric spatial (spatio-temporal) geostatistics. S3 classes and methods for multidimensional: linear binning, local polynomial kernel regression (spatial trend estimation), density and variogram estimation. Nonparametric methods for simultaneous inference on both spatial trend and variogram functions (for spatial processes). Nonparametric residual kriging (spatial prediction). For details on these methods see, for example, Fernandez-Casal and Francisco-Fernandez (2014) <doi:10.1007/s00477-013-0817-8> or Castillo-Paez et al. (2019) <doi:10.1016/j.csda.2019.01.017>.

Maintained by Ruben Fernandez-Casal. Last updated 4 months ago.

geostatistics spatial-data-analysis statistics fortran openblas

0.8 match 4 stars 5.71 score 64 scripts

alexanderrobitzsch

CDM:Cognitive Diagnosis Modeling

Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. This package enables the estimation of the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>), the multiple group (polytomous) GDINA model (de la Torre, 2011, <doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009, <doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008, <doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992, <doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis (Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>). See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02> or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>) for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as Ravand and Robitzsch (2015).

Maintained by Alexander Robitzsch. Last updated 9 months ago.

cognitive-diagnostic-models item-response-theory cpp

0.5 match 22 stars 8.76 score 138 scripts 28 dependents

dvrbts

fso:Fuzzy Set Ordination

Fuzzy set ordination is a multivariate analysis used in ecology to relate the composition of samples to possible explanatory variables. While differing in theory and method, in practice, the use is similar to 'constrained ordination.' The package contains plotting and summary functions as well as the analyses.

Maintained by David W. Roberts. Last updated 2 years ago.

fortran

3.6 match 1.18 score 15 scripts

r-forge

stops:Structure Optimized Proximity Scaling

Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on goodness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices.

Maintained by Thomas Rusch. Last updated 2 months ago.

openjdk

0.9 match 1 stars 4.48 score 23 scripts

jdtuck

fdasrvf:Elastic Functional Data Analysis

Performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 <doi:10.48550/arXiv.1103.3817> and Tucker et al., 2014 <DOI:10.1016/j.csda.2012.12.001>). This framework allows for elastic analysis of functional data through phase and amplitude separation.

Maintained by J. Derek Tucker. Last updated 27 days ago.

openblas cpp openmp

0.5 match 11 stars 7.74 score 83 scripts 3 dependents

rikenbit

rTensor:Tools for Tensor Analysis and Decomposition

A set of tools for creation, manipulation, and modeling of tensors with arbitrary number of modes. A tensor in the context of data analysis is a multidimensional array. rTensor does this by providing a S4 class 'Tensor' that wraps around the base 'array' class. rTensor provides common tensor operations as methods, including matrix unfolding, summing/averaging across modes, calculating the Frobenius norm, and taking the inner product between two tensors. Familiar array operations are overloaded, such as index subsetting via '[' and element-wise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao product, Kronecker product, and the Hadamard product for a list of matrices.

Maintained by Koki Tsuyuzaki. Last updated 2 years ago.

0.5 match 6 stars 7.65 score 278 scripts 30 dependents

cran

pmr:Probability Models for Ranking Data

Descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce models, distance-based models, and rank-ordered logit models) and visualization with multidimensional preference analysis for ranking data are provided. Current, only complete rankings are supported by this package.

Maintained by Paul H. Lee. Last updated 3 years ago.

2.5 match 1.48 score 1 dependents

aybekec

RSP:'shiny' Applications for Statistical and Psychometric Analysis

Toolbox with 'shiny' applications for widely used psychometric methods. Those methods include following analysis: Item analysis, item response theory calibration, principal component analysis, confirmatory factor analysis - structural equation modeling, generating simulated data. References: Chalmers (2012, <doi:10.18637/jss.v048.i06>); Revelle (2022, <https://CRAN.R-project.org/package=psych Version = 2.2.9.>); Rosseel (2012, <doi:10.18637/jss.v048.i02>); Magis & Raiche (2012, <doi:10.18637/jss.v048.i08>); Magis & Barrada (2017, <doi:10.18637/jss.v076.c01>).

Maintained by Eren Can Aybek. Last updated 1 years ago.

openjdk

1.6 match 2.28 score 19 scripts

bioc

mitch:Multi-Contrast Gene Set Enrichment Analysis

mitch is an R package for multi-contrast enrichment analysis. At it’s heart, it uses a rank-MANOVA based statistical approach to detect sets of genes that exhibit enrichment in the multidimensional space as compared to the background. The rank-MANOVA concept dates to work by Cox and Mann (https://doi.org/10.1186/1471-2105-13-S16-S12). mitch is useful for pathway analysis of profiling studies with one, two or more contrasts, or in studies with multiple omics profiling, for example proteomic, transcriptomic, epigenomic analysis of the same samples. mitch is perfectly suited for pathway level differential analysis of scRNA-seq data. We have an established routine for pathway enrichment of Infinium Methylation Array data (see vignette). The main strengths of mitch are that it can import datasets easily from many upstream tools and has advanced plotting features to visualise these enrichments.

Maintained by Mark Ziemann. Last updated 4 months ago.

geneexpression genesetenrichment singlecell transcriptomics epigenetics proteomics differentialexpression reactome dnamethylation methylationarray gene-regulation gene-seq-analysis pathway-analysis

0.5 match 16 stars 7.06 score 15 scripts

carolynanderson

pleLMA:Pseudo-Likelihood Estimation of Log-Multiplicative Association Models

Log-multiplicative association models (LMA) are models for cross-classifications of categorical variables where interactions are represented by products of category scale values and an association parameter. Maximum likelihood estimation (MLE) fails for moderate to large numbers of categorical variables. The 'pleLMA' package overcomes this limitation of MLE by using pseudo-likelihood estimation to fit the models to small or large cross-classifications dichotomous or multi-category variables. Originally proposed by Besag (1974, <doi:10.1111/j.2517-6161.1974.tb00999.x>), pseudo-likelihood estimation takes large complex models and breaks it down into smaller ones. Rather than maximizing the likelihood of the joint distribution of all the variables, a pseudo-likelihood function, which is the product likelihoods from conditional distributions, is maximized. LMA models can be derived from a number of different frameworks including (but not limited to) graphical models and uni-dimensional and multi-dimensional item response theory models. More details about the models and estimation can be found in the vignette.

Maintained by Carolyn J. Anderson. Last updated 3 years ago.

1.7 match 2.04 score 11 scripts