R-universe search: exports:print

rspatial

raster:Geographic Data Analysis and Modeling

Reading, writing, manipulating, analyzing and modeling of spatial data. This package has been superseded by the "terra" package <https://CRAN.R-project.org/package=terra>.

Maintained by Robert J. Hijmans. Last updated 2 days ago.

cpp

163 stars 17.23 score 58k scripts 562 dependents

r-forge

Matrix:Sparse and Dense Matrix Classes and Methods

A rich hierarchy of sparse and dense matrix classes, including general, symmetric, triangular, and diagonal matrices with numeric, logical, or pattern entries. Efficient methods for operating on such matrices, often wrapping the 'BLAS', 'LAPACK', and 'SuiteSparse' libraries.

Maintained by Martin Maechler. Last updated 20 days ago.

openblas

1 stars 17.23 score 33k scripts 12k dependents

quanteda

quanteda:Quantitative Analysis of Textual Data

A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and n-grams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.

Maintained by Kenneth Benoit. Last updated 3 months ago.

corpus natural-language-processing quanteda text-analytics onetbb cpp

851 stars 16.65 score 5.4k scripts 52 dependents

biomodhub

biomod2:Ensemble Platform for Species Distribution Modeling

Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualisation tools are also available within the package.

Maintained by Maya Guéguen. Last updated 1 days ago.

95 stars 13.85 score 536 scripts 7 dependents

knausb

vcfR:Manipulate and Visualize VCF Data

Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.

Maintained by Brian J. Knaus. Last updated 1 months ago.

genomics population-genetics population-genomics rcpp vcf-data visualization zlib cpp

256 stars 13.66 score 3.1k scripts 19 dependents

eddelbuettel

inline:Functions to Inline C, C++, Fortran Function Calls from R

Functionality to dynamically define R functions and S4 methods with 'inlined' C, C++ or Fortran code supporting the .C and .Call calling conventions.

Maintained by Dirk Eddelbuettel. Last updated 2 months ago.

fortran rcpp

43 stars 13.11 score 576 scripts 333 dependents

alexkowa

EnvStats:Package for Environmental Statistics, Including US EPA Guidance

Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).

Maintained by Alexander Kowarik. Last updated 29 days ago.

26 stars 12.80 score 2.4k scripts 46 dependents

spedygiorgio

markovchain:Easy Handling Discrete Time Markov Chains

Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.

Maintained by Giorgio Alfredo Spedicato. Last updated 5 months ago.

ctmc dtmc markov-chain markov-model r-programming rcpp openblas cpp

104 stars 12.78 score 712 scripts 4 dependents

melff

memisc:Management of Survey Data and Presentation of Analysis Results

An infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) 'SPSS' and 'Stata' files is provided. Further, the package allows to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates, which can be exported to 'LaTeX' and HTML.

Maintained by Martin Elff. Last updated 24 days ago.

survey-data

46 stars 12.34 score 1.2k scripts 13 dependents

miraisolutions

XLConnect:Excel Connector for R

Provides comprehensive functionality to read, write and format Excel data.

Maintained by Martin Studer. Last updated 30 days ago.

cross-platform excel r-language xlconnect openjdk

130 stars 12.17 score 1.2k scripts 1 dependents

kaneplusplus

bigmemory:Manage Massive Matrices with Shared Memory and Memory-Mapped Files

Create, store, access, and manipulate massive matrices. Matrices are allocated to shared memory and may use memory-mapped files. Packages 'biganalytics', 'bigtabulate', 'synchronicity', and 'bigalgebra' provide advanced functionality.

Maintained by Michael J. Kane. Last updated 1 years ago.

cpp

127 stars 11.87 score 920 scripts 64 dependents

kingaa

pomp:Statistical Inference for Partially Observed Markov Processes

Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.

Maintained by Aaron A. King. Last updated 9 days ago.

abc b-spline differential-equations dynamical-systems iterated-filtering likelihood likelihood-free markov-chain-monte-carlo markov-model mathematical-modelling measurement-error particle-filter sequential-monte-carlo simulation-based-inference sobol-sequence state-space statistical-inference stochastic-processes time-series openblas

114 stars 11.74 score 1.3k scripts 4 dependents

luca-scr

GA:Genetic Algorithms

Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach. For more details see Scrucca (2013) <doi:10.18637/jss.v053.i04> and Scrucca (2017) <doi:10.32614/RJ-2017-008>.

Maintained by Luca Scrucca. Last updated 7 months ago.

genetic-algorithm optimisation cpp

93 stars 11.58 score 624 scripts 52 dependents

bioc

msa:Multiple Sequence Alignment

The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.

Maintained by Ulrich Bodenhofer. Last updated 1 months ago.

multiplesequencealignment alignment multiplecomparison sequencing cpp

17 stars 11.46 score 744 scripts 6 dependents

bioc

destiny:Creates diffusion maps

Create and plot diffusion maps.

Maintained by Philipp Angerer. Last updated 4 months ago.

cellbiology cellbasedassays clustering software visualization diffusion-maps dimensionality-reduction cpp

82 stars 11.44 score 792 scripts 1 dependents

bioc

ggcyto:Visualize Cytometry data with ggplot

With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. ggcyto wrapper and some customed layers also make it easy to add gates and population statistics to the plot.

Maintained by Mike Jiang. Last updated 5 months ago.

immunooncology flowcytometry cellbasedassays infrastructure visualization

58 stars 11.25 score 362 scripts 5 dependents

fmichonneau

phylobase:Base Package for Phylogenetic Structures and Comparative Data

Provides a base S4 class for comparative methods, incorporating one or more trees and trait data.

Maintained by Francois Michonneau. Last updated 1 years ago.

phylogenetics cpp

18 stars 11.10 score 394 scripts 18 dependents

r-forge

MatrixModels:Modelling with Sparse and Dense Matrices

Generalized Linear Modelling with sparse and dense 'Matrix' matrices, using modular prediction and response module classes.

Maintained by Martin Maechler. Last updated 21 hours ago.

1 stars 10.91 score 1.5k dependents

eddelbuettel

nanotime:Nanosecond-Resolution Time Support for R

Full 64-bit resolution date and time functionality with nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type. Three additional classes offer interval, period and duration functionality for nanosecond-resolution timestamps.

Maintained by Dirk Eddelbuettel. Last updated 2 months ago.

datetime datetimes nanosecond-resolution nanoseconds cpp

53 stars 10.91 score 134 scripts 17 dependents

grunwaldlab

poppr:Genetic Analysis of Populations with Mixed Reproduction

Population genetic analyses for hierarchical analysis of partially clonal populations built upon the architecture of the 'adegenet' package. Originally described in Kamvar, Tabima, and Grünwald (2014) <doi:10.7717/peerj.281> with version 2.0 described in Kamvar, Brooks, and Grünwald (2015) <doi:10.3389/fgene.2015.00208>.

Maintained by Zhian N. Kamvar. Last updated 11 months ago.

clonality genetic-analysis genetic-distances minimum-spanning-networks multilocus-genotypes multilocus-lineages population-genetics populations openmp

69 stars 10.84 score 672 scripts

wrathematics

float:32-Bit Floats

R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.

Maintained by Drew Schmidt. Last updated 20 days ago.

float-matrix hpc linear-algebra matrix fortran openblas openmp

46 stars 10.53 score 228 scripts 42 dependents

wrathematics

ngram:Fast n-Gram 'Tokenization'

An n-gram is a sequence of n "words" taken, in order, from a body of text. This is a collection of utilities for creating, displaying, summarizing, and "babbling" n-grams. The 'tokenization' and "babbling" are handled by very efficient C code, which can even be built as its own standalone library. The babbler is a simple Markov chain. The package also offers a vignette with complete example 'workflows' and information about the utilities offered in the package.

Maintained by Drew Schmidt. Last updated 1 years ago.

ngram text text-mining

71 stars 10.45 score 844 scripts 7 dependents

adeverse

adegraphics:An S4 Lattice-Based Package for the Representation of Multivariate Data

Graphical functionalities for the representation of multivariate data. It is a complete re-implementation of the functions available in the 'ade4' package.

Maintained by Aurélie Siberchicot. Last updated 8 months ago.

9 stars 10.37 score 386 scripts 6 dependents

ssnn-airr

alakazam:Immunoglobulin Clonal Lineage and Diversity Analysis

Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.

Maintained by Susanna Marquez. Last updated 3 months ago.

software annotationdata cpp

10.33 score 424 scripts 7 dependents

bioc

flowCore:flowCore: Basic structures for flow cytometry data

Provides S4 data structures and basic functions to deal with flow cytometry data.

Maintained by Mike Jiang. Last updated 5 months ago.

immunooncology infrastructure flowcytometry cellbasedassays cpp

10.17 score 1.7k scripts 59 dependents

robinhankin

partitions:Additive Partitions of Integers

Additive partitions of integers. Enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given. Set partitions and now compositions and riffle shuffles are included.

Maintained by Robin K. S. Hankin. Last updated 7 months ago.

cpp

9 stars 10.04 score 191 scripts 78 dependents

shinra-dev

memuse:Memory Estimation Utilities

How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have? Learn the scintillating answer to these and many more such questions with the 'memuse' package.

Maintained by Drew Schmidt. Last updated 2 years ago.

memory-estimation

46 stars 9.84 score 142 scripts 33 dependents

sdctools

sdcMicro:Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation

Data from statistical agencies and other institutions are mostly confidential. This package, introduced in Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>, can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymization methods are included. Note that the package includes a graphical user interface published in Meindl and Templ (2019) <doi:10.3390/a12090191> that allows to use various methods of this package.

Maintained by Matthias Templ. Last updated 1 months ago.

cpp

84 stars 9.63 score 258 scripts

reinhardfurrer

spam:SPArse Matrix

Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.

Maintained by Reinhard Furrer. Last updated 2 months ago.

fortran openblas cpp

1 stars 9.36 score 420 scripts 439 dependents

david-cortes

MatrixExtra:Extra Methods for Sparse Matrices

Extends sparse matrix and vector classes from the 'Matrix' package by providing: (a) Methods and operators that work natively on CSR formats (compressed sparse row, a.k.a. 'RsparseMatrix') such as slicing/sub-setting, assignment, rbind(), mathematical operators for CSR and COO such as addition ("+") or sqrt(), and methods such as diag(); (b) Multi-threaded matrix multiplication and cross-product for many <sparse, dense> types, including the 'float32' type from 'float'; (c) Coercion methods between pairs of classes which are not present in 'Matrix', such as 'dgCMatrix' -> 'ngRMatrix', as well as convenience conversion functions; (d) Utility functions for sparse matrices such as sorting the indices or removing zero-valued entries; (e) Fast transposes that work by outputting in the opposite storage format; (f) Faster replacements for many 'Matrix' methods for all sparse types, such as slicing and elementwise multiplication. (g) Convenience functions for sparse objects, such as 'mapSparse' or a shorter 'show' method.

Maintained by David Cortes. Last updated 9 months ago.

csr sparse-matrix openblas cpp openmp

20 stars 9.08 score 84 scripts 29 dependents

bioc

topGO:Enrichment Analysis for Gene Ontology

topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

Maintained by Adrian Alexa. Last updated 5 months ago.

microarray visualization

8.96 score 2.0k scripts 20 dependents

flr

FLCore:Core Package of FLR, Fisheries Modelling in R

Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.

Maintained by Iago Mosqueira. Last updated 9 days ago.

fisheries flr fisheries-modelling

16 stars 8.78 score 956 scripts 23 dependents

r-forge

distr:Object Oriented Implementation of Distributions

S4-classes and methods for distributions.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

8.77 score 327 scripts 32 dependents

bioc

ReactomeGSA:Client for the Reactome Analysis Service for comparative multi-omics gene set analysis

The ReactomeGSA packages uses Reactome's online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME's powerful webapplication. Since Reactome's analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.

Maintained by Johannes Griss. Last updated 4 months ago.

genesetenrichment proteomics transcriptomics systemsbiology geneexpression reactome

22 stars 8.50 score 67 scripts 1 dependents

hmorlon

RPANDA:Phylogenetic ANalyses of DiversificAtion

Implements macroevolutionary analyses on phylogenetic trees. See Morlon et al. (2010) <DOI:10.1371/journal.pbio.1000493>, Morlon et al. (2011) <DOI:10.1073/pnas.1102543108>, Condamine et al. (2013) <DOI:10.1111/ele.12062>, Morlon et al. (2014) <DOI:10.1111/ele.12251>, Manceau et al. (2015) <DOI:10.1111/ele.12415>, Lewitus & Morlon (2016) <DOI:10.1093/sysbio/syv116>, Drury et al. (2016) <DOI:10.1093/sysbio/syw020>, Manceau et al. (2016) <DOI:10.1093/sysbio/syw115>, Morlon et al. (2016) <DOI:10.1111/2041-210X.12526>, Clavel & Morlon (2017) <DOI:10.1073/pnas.1606868114>, Drury et al. (2017) <DOI:10.1093/sysbio/syx079>, Lewitus & Morlon (2017) <DOI:10.1093/sysbio/syx095>, Drury et al. (2018) <DOI:10.1371/journal.pbio.2003563>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045>, Maliet et al. (2019) <DOI:10.1038/s41559-019-0908-0>, Billaud et al. (2019) <DOI:10.1093/sysbio/syz057>, Lewitus et al. (2019) <DOI:10.1093/sysbio/syz061>, Aristide & Morlon (2019) <DOI:10.1111/ele.13385>, Maliet et al. (2020) <DOI:10.1111/ele.13592>, Drury et al. (2021) <DOI:10.1371/journal.pbio.3001270>, Perez-Lamarque & Morlon (2022) <DOI:10.1111/mec.16478>, Perez-Lamarque et al. (2022) <DOI:10.1101/2021.08.30.458192>, Mazet et al. (2023) <DOI:10.1111/2041-210X.14195>, Drury et al. (2024) <DOI:10.1016/j.cub.2023.12.055>.

Maintained by Hélène Morlon. Last updated 3 months ago.

24 stars 8.50 score 255 scripts

bioc

dreamlet:Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs

Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of these data, complex study designs, and low read count per cell mean that characterizing cell type specific molecular mechanisms requires a user-frieldly, purpose-build analytical framework. We have developed the dreamlet package that applies a pseudobulk approach and fits a regression model for each gene and cell cluster to test differential expression across individuals associated with a trait of interest. Use of precision-weighted linear mixed models enables accounting for repeated measures study designs, high dimensional batch effects, and varying sequencing depth or observed cells per biosample.

Maintained by Gabriel Hoffman. Last updated 4 days ago.

rnaseq geneexpression differentialexpression batcheffect qualitycontrol regression genesetenrichment generegulation epigenetics functionalgenomics transcriptomics normalization singlecell preprocessing sequencing immunooncology software cpp

12 stars 8.14 score 128 scripts

r-hyperspec

hyperSpec:Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

Comfortable ways to work with hyperspectral data sets, i.e. spatially or time-resolved spectra, or spectra with any other kind of information associated with each of the spectra. The spectra can be data as obtained in XRF, UV/VIS, Fluorescence, AES, NIR, IR, Raman, NMR, MS, etc. More generally, any data that is recorded over a discretized variable, e.g. absorbance = f(wavelength), stored as a vector of absorbance values for discrete wavelengths is suitable.

Maintained by Claudia Beleites. Last updated 10 months ago.

data-wrangling hyperspectral imaging infrared nmr raman spectroscopy uv-vis xrf

16 stars 8.10 score 233 scripts 2 dependents

robinhankin

hyper2:The Hyperdirichlet Distribution, Mark 2

A suite of routines for the hyperdirichlet distribution and reified Bradley-Terry; supersedes the 'hyperdirichlet' package; uses 'disordR' discipline <doi:10.48550/ARXIV.2210.03856>. To cite in publications please use Hankin 2017 <doi:10.32614/rj-2017-061>, and for Generalized Plackett-Luce likelihoods use Hankin 2024 <doi:10.18637/jss.v109.i08>.

Maintained by Robin K. S. Hankin. Last updated 5 hours ago.

cpp

5 stars 7.91 score 38 scripts 1 dependents

bioc

siggenes:Multiple Testing using SAM and Efron's Empirical Bayes Approaches

Identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM).

Maintained by Holger Schwender. Last updated 5 months ago.

multiplecomparison microarray geneexpression snp exonarray differentialexpression

7.87 score 74 scripts 34 dependents

adamlilith

fasterRaster:Faster Raster and Spatial Vector Processing Using 'GRASS GIS'

Processing of large-in-memory/large-on disk rasters and spatial vectors using 'GRASS GIS' <https://grass.osgeo.org/>. Most functions in the 'terra' package are recreated. Processing of medium-sized and smaller spatial objects will nearly always be faster using 'terra' or 'sf', but for large-in-memory/large-on-disk objects, 'fasterRaster' may be faster. To use most of the functions, you must have the stand-alone version (not the 'OSGeoW4' installer version) of 'GRASS GIS' 8.0 or higher.

Maintained by Adam B. Smith. Last updated 3 days ago.

aspect distance fragmentation fragmentation-indices gis grass grass-gis raster raster-projection rasterize slope topography vectorization

57 stars 7.68 score 8 scripts

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.

6 stars 7.65 score 278 scripts 30 dependents

bioc

ropls:PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data

Latent variable modeling with Principal Component Analysis (PCA) and Partial Least Squares (PLS) are powerful methods for visualization, regression, classification, and feature selection of omics data where the number of variables exceeds the number of samples and with multicollinearity among variables. Orthogonal Partial Least Squares (OPLS) enables to separately model the variation correlated (predictive) to the factor of interest and the uncorrelated (orthogonal) variation. While performing similarly to PLS, OPLS facilitates interpretation. Successful applications of these chemometrics techniques include spectroscopic data such as Raman spectroscopy, nuclear magnetic resonance (NMR), mass spectrometry (MS) in metabolomics and proteomics, but also transcriptomics data. In addition to scores, loadings and weights plots, the package provides metrics and graphics to determine the optimal number of components (e.g. with the R2 and Q2 coefficients), check the validity of the model by permutation testing, detect outliers, and perform feature selection (e.g. with Variable Importance in Projection or regression coefficients). The package can be accessed via a user interface on the Workflow4Metabolomics.org online resource for computational metabolomics (built upon the Galaxy environment).

Maintained by Etienne A. Thevenot. Last updated 5 months ago.

regression classification principalcomponent transcriptomics proteomics metabolomics lipidomics massspectrometry immunooncology

7.55 score 210 scripts 8 dependents

ropensci

rsat:Dealing with Multiplatform Satellite Images

Downloading, customizing, and processing time series of satellite images for a region of interest. 'rsat' functions allow a unified access to multispectral images from Landsat, MODIS and Sentinel repositories. 'rsat' also offers capabilities for customizing satellite images, such as tile mosaicking, image cropping and new variables computation. Finally, 'rsat' covers the processing, including cloud masking, compositing and gap-filling/smoothing time series of images (Militino et al., 2018 <doi:10.3390/rs10030398> and Militino et al., 2019 <doi:10.1109/TGRS.2019.2904193>).

Maintained by Unai Pérez - Goya. Last updated 12 months ago.

satellite-images

54 stars 7.45 score 52 scripts

ssnn-airr

shazam:Immunoglobulin Somatic Hypermutation Analysis

Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.

Maintained by Susanna Marquez. Last updated 3 months ago.

7.43 score 222 scripts 2 dependents

spatpomp-org

spatPomp:Inference for Spatiotemporal Partially Observed Markov Processes

Inference on panel data using spatiotemporal partially-observed Markov process (SpatPOMP) models. The 'spatPomp' package extends 'pomp' to include algorithms taking advantage of the spatial structure in order to assist with handling high dimensional processes. See Asfaw et al. (2024) <doi:10.48550/arXiv.2101.01157> for further description of the package.

Maintained by Edward Ionides. Last updated 5 months ago.

2 stars 7.38 score 93 scripts

choi-phd

TestDesign:Optimal Test Design Approach to Fixed and Adaptive Test Construction

Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> to construct fixed, adaptive, and parallel tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>.

Maintained by Seung W. Choi. Last updated 6 months ago.

openblas cpp

3 stars 7.34 score 37 scripts 2 dependents

bips-hb

innsight:Get the Insights of Your Neural Network

Interpretation methods for analyzing the behavior and individual predictions of modern neural networks in a three-step procedure: Converting the model, running the interpretation method, and visualizing the results. Implemented methods are, e.g., 'Connection Weights' described by Olden et al. (2004) <doi:10.1016/j.ecolmodel.2004.03.013>, layer-wise relevance propagation ('LRP') described by Bach et al. (2015) <doi:10.1371/journal.pone.0130140>, deep learning important features ('DeepLIFT') described by Shrikumar et al. (2017) <doi:10.48550/arXiv.1704.02685> and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) <doi:10.48550/arXiv.1706.03825>, 'Gradient x Input' or 'Vanilla Gradient'. Details can be found in the accompanying scientific paper: Koenen & Wright (2024, Journal of Statistical Software, <doi:10.18637/jss.v111.i08>).

Maintained by Niklas Koenen. Last updated 1 days ago.

30 stars 7.31 score 57 scripts

kornl

gMCP:Graph Based Multiple Comparison Procedures

Functions and a graphical user interface for graphical described multiple test procedures.

Maintained by Kornelius Rohmeyer. Last updated 1 years ago.

openjdk

10 stars 7.31 score 105 scripts 2 dependents

ropensci

melt:Multiple Empirical Likelihood Tests

Performs multiple empirical likelihood tests. It offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences. The core computational routines are implemented using the 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for parallel computation. Details of the testing procedures are provided in Kim, MacEachern, and Peruggia (2023) <doi:10.1080/10485252.2023.2206919>. A companion paper by Kim, MacEachern, and Peruggia (2024) <doi:10.18637/jss.v108.i05> is available for further information. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.

Maintained by Eunseop Kim. Last updated 11 months ago.

cpp openmp

12 stars 7.24 score 84 scripts

vpihur

clValid:Validation of Clustering Results

Statistical and biological validation of clustering results. This package implements Dunn Index, Silhouette, Connectivity, Stability, BHI and BSI. Further information can be found in Brock, G et al. (2008) <doi: 10.18637/jss.v025.i04>.

Maintained by Vasyl Pihur. Last updated 4 years ago.

5 stars 7.24 score 422 scripts 14 dependents

datastorm-open

rAmCharts:JavaScript Charts Tool

Provides an R interface for using 'AmCharts' Library. Based on 'htmlwidgets', it provides a global architecture to generate 'JavaScript' source code for charts. Most of classes in the library have their equivalent in R with S4 classes; for those classes, not all properties have been referenced but can easily be added in the constructors. Complex properties (e.g. 'JavaScript' object) can be passed as named list. See examples at <https://datastorm-open.github.io/introduction_ramcharts/> and <https://www.amcharts.com/> for more information about the library. The package includes the free version of 'AmCharts' Library. Its only limitation is a small link to the web site displayed on your charts. If you enjoy this library, do not hesitate to refer to this page <https://www.amcharts.com/online-store/> to purchase a licence, and thus support its creators and get a period of Priority Support. See also <https://www.amcharts.com/about/> for more information about 'AmCharts' company.

Maintained by Benoit Thieurmel. Last updated 3 months ago.

49 stars 7.17 score 153 scripts 4 dependents

ropensci

taxlist:Handling Taxonomic Lists

Handling taxonomic lists through objects of class 'taxlist'. This package provides functions to import species lists from 'Turboveg' (<https://www.synbiosys.alterra.nl/turboveg/>) and the possibility to create backups from resulting R-objects. Also quick displays are implemented as summary-methods.

Maintained by Miguel Alvarez. Last updated 6 months ago.

12 stars 7.07 score 81 scripts 2 dependents

spedygiorgio

lifecontingencies:Financial and Actuarial Mathematics for Life Contingencies

Classes and methods that allow the user to manage life table, actuarial tables (also multiple decrements tables). Moreover, functions to easily perform demographic, financial and actuarial mathematics on life contingencies insurances calculations are contained therein. See Spedicato (2013) <doi:10.18637/jss.v055.i10>.

Maintained by Giorgio Alfredo Spedicato. Last updated 6 months ago.

actuarial financial life-contingencies life-insurance cpp

61 stars 7.06 score 156 scripts

doccstat

fastcpd:Fast Change Point Detection via Sequential Gradient Descent

Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.

Maintained by Xingchi Li. Last updated 12 days ago.

change-point-detection cpp custom-function gradient-descent lasso linear-regression logistic-regression offline pelt penalized-regression poisson-regression quasi-newton statistics time-series warm-start fortran openblas cpp openmp

22 stars 7.00 score 7 scripts

r-forge

oompaBase:Class Unions, Matrix Operations, and Color Schemes for OOMPA

Provides the class unions that must be preloaded in order for the basic tools in the OOMPA (Object-Oriented Microarray and Proteomics Analysis) project to be defined and loaded. It also includes vectorized operations for row-by-row means, variances, and t-tests. Finally, it provides new color schemes. Details on the packages in the OOMPA project can be found at <http://oompa.r-forge.r-project.org/>.

Maintained by Kevin R. Coombes. Last updated 2 months ago.

infrastructure

6.97 score 29 scripts 18 dependents

skoval

RISmed:Download Content from NCBI Databases

A set of tools to extract bibliographic content from the National Center for Biotechnology Information (NCBI) databases, including PubMed. The name RISmed is a portmanteau of RIS (for Research Information Systems, a common tag format for bibliographic data) and PubMed.

Maintained by Stephanie Kovalchik. Last updated 3 years ago.

38 stars 6.94 score 252 scripts 3 dependents

unuran

Runuran:R Interface to the 'UNU.RAN' Random Variate Generators

Interface to the 'UNU.RAN' library for Universal Non-Uniform RANdom variate generators. Thus it allows to build non-uniform random number generators from quite arbitrary distributions. In particular, it provides an algorithm for fast numerical inversion for distribution with given density function. In addition, the package contains densities, distribution functions and quantiles from a couple of distributions.

Maintained by Josef Leydold. Last updated 6 months ago.

6.87 score 180 scripts 8 dependents

kingaa

ouch:Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses

Fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.

Maintained by Aaron A. King. Last updated 5 months ago.

adaptive-regime brownian-motion ornstein-uhlenbeck ornstein-uhlenbeck-models ouch phylogenetic-comparative-hypotheses phylogenetic-comparative-methods phylogenetic-data react

15 stars 6.87 score 68 scripts 4 dependents

pbs-software

PBSmodelling:GUI Tools Made Easy: Interact with Models and Explore Data

Provides software to facilitate the design, testing, and operation of computer models. It focuses particularly on tools that make it easy to construct and edit a customized graphical user interface ('GUI'). Although our simplified 'GUI' language depends heavily on the R interface to the 'Tcl/Tk' package, a user does not need to know 'Tcl/Tk'. Examples illustrate models built with other R packages, including 'PBSmapping', 'PBSddesolve', and 'BRugs'. A complete user's guide 'PBSmodelling-UG.pdf' shows how to use this package effectively.

Maintained by Rowan Haigh. Last updated 5 months ago.

2 stars 6.76 score 120 scripts 4 dependents

bioc

doppelgangR:Identify likely duplicate samples from genomic or meta-data

The main function is doppelgangR(), which takes as minimal input a list of ExpressionSet object, and searches all list pairs for duplicated samples. The search is based on the genomic data (exprs(eset)), phenotype/clinical data (pData(eset)), and "smoking guns" - supposedly unique identifiers found in pData(eset).

Maintained by Levi Waldron. Last updated 5 months ago.

immunooncology rnaseq microarray geneexpression qualitycontrol bioconductor-package

5 stars 6.67 score 31 scripts

r-forge

distrMod:Object Oriented Implementation of Probability Models

Implements S4 classes for probability models based on packages 'distr' and 'distrEx'.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

6.60 score 139 scripts 6 dependents

markbravington

mvbutils:General utilities, workspace organization, code and docu editing, live package maintenance, etc

Hierarchical workspace tree, code editing and backup, easy package prep, editing of packages while loaded, per-object lazy-loading, easy documentation, macro functions, and miscellaneous utilities. Needed by debug package.

Maintained by Mark V. Bravington. Last updated 4 days ago.

6.57 score 138 scripts 18 dependents

fbertran

Cascade:Selection, Reverse-Engineering and Prediction in Cascade Networks

A modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.

Maintained by Frederic Bertrand. Last updated 2 years ago.

1 stars 6.56 score 40 scripts 2 dependents

bioc

GeneOverlap:Test and visualize gene overlaps

Test two sets of gene lists and visualize the results.

Maintained by António Miguel de Jesus Domingues, Max-Planck Institute for Cell Biology and Genetics. Last updated 5 months ago.

multiplecomparison visualization

6.46 score 266 scripts

r-forge

TailRank:The Tail-Rank Statistic

Implements the tail-rank statistic for selecting biomarkers from a microarray data set, an efficient nonparametric test focused on the distributional tails. See <https://gitlab.com/krcoombes/coombeslab/-/blob/master/doc/papers/tolstoy-new.pdf>.

Maintained by Kevin R. Coombes. Last updated 2 months ago.

6.38 score 37 scripts 3 dependents

smoeding

usl:Analyze System Scalability with the Universal Scalability Law

The Universal Scalability Law (Gunther 2007) <doi:10.1007/978-3-540-31010-5> is a model to predict hardware and software scalability. It uses system capacity as a function of load to forecast the scalability for the system.

Maintained by Stefan Moeding. Last updated 3 years ago.

scalability universal-scalability-law usl

36 stars 6.32 score 117 scripts

larmarange

prevR:Estimating Regional Trends of a Prevalence from a DHS and Similar Surveys

Spatial estimation of a prevalence surface or a relative risks surface, using data from a Demographic and Health Survey (DHS) or an analog survey, see Larmarange et al. (2011) <doi:10.4000/cybergeo.24606>.

Maintained by Joseph Larmarange. Last updated 6 months ago.

5 stars 6.26 score 46 scripts

bioc

dominoSignal:Cell Communication Analysis for Single Cell RNA Sequencing

dominoSignal is a package developed to analyze cell signaling through ligand - receptor - transcription factor networks in scRNAseq data. It takes as input information transcriptomic data, requiring counts, z-scored counts, and cluster labels, as well as information on transcription factor activation (such as from SCENIC) and a database of ligand and receptor pairings (such as from CellPhoneDB). This package creates an object storing ligand - receptor - transcription factor linkages by cluster and provides several methods for exploring, summarizing, and visualizing the analysis.

Maintained by Jacob T Mitchell. Last updated 12 days ago.

systemsbiology singlecell transcriptomics network

5 stars 6.20 score 5 scripts

bioc

GPA:GPA (Genetic analysis incorporating Pleiotropy and Annotation)

This package provides functions for fitting GPA, a statistical framework to prioritize GWAS results by integrating pleiotropy information and annotation data. In addition, it also includes ShinyGPA, an interactive visualization toolkit to investigate pleiotropic architecture.

Maintained by Dongjun Chung. Last updated 5 months ago.

software statisticalmethod classification genomewideassociation snp genetics clustering multiplecomparison preprocessing geneexpression differentialexpression cpp

14 stars 6.15 score 7 scripts

bioc

qcmetrics:A Framework for Quality Control

The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.

Maintained by Laurent Gatto. Last updated 5 months ago.

immunooncology software qualitycontrol proteomics microarray massspectrometry visualization reportwriting

2 stars 6.03 score 2 dependents

bioc

normr:Normalization and difference calling in ChIP-seq data

Robust normalization and difference calling procedures for ChIP-seq and alike data. Read counts are modeled jointly as a binomial mixture model with a user-specified number of components. A fitted background estimate accounts for the effect of enrichment in certain regions and, therefore, represents an appropriate null hypothesis. This robust background is used to identify significantly enriched or depleted regions.

Maintained by Johannes Helmuth. Last updated 5 months ago.

bayesian differentialpeakcalling classification dataimport chipseq ripseq functionalgenomics genetics multiplecomparison normalization peakdetection preprocessing alignment cpp openmp

11 stars 5.93 score 13 scripts

jeswheel

panelPomp:Inference for Panel Partially Observed Markov Processes

Data analysis based on panel partially-observed Markov process (PanelPOMP) models. To implement such models, simulate them and fit them to panel data, 'panelPomp' extends some of the facilities provided for time series data by the 'pomp' package. Implemented methods include filtering (panel particle filtering) and maximum likelihood estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) "Panel Data Analysis via Mechanistic Models" <doi:10.1080/01621459.2019.1604367>.

Maintained by Jesse Wheeler. Last updated 4 months ago.

5.91 score 45 scripts

bozenne

BuyseTest:Generalized Pairwise Comparisons

Implementation of the Generalized Pairwise Comparisons (GPC) as defined in Buyse (2010) <doi:10.1002/sim.3923> for complete observations, and extended in Peron (2018) <doi:10.1177/0962280216658320> to deal with right-censoring. GPC compare two groups of observations (intervention vs. control group) regarding several prioritized endpoints to estimate the probability that a random observation drawn from one group performs better/worse/equivalently than a random observation drawn from the other group. Summary statistics such as the net treatment benefit, win ratio, or win odds are then deduced from these probabilities. Confidence intervals and p-values are obtained based on asymptotic results (Ozenne 2021 <doi:10.1177/09622802211037067>), non-parametric bootstrap, or permutations. The software enables the use of thresholds of minimal importance difference, stratification, non-prioritized endpoints (O Brien test), and can handle right-censoring and competing-risks.

Maintained by Brice Ozenne. Last updated 17 days ago.

generalized-pairwise-comparisons non-parametric statistics cpp

5 stars 5.91 score 90 scripts

ropensci

phylotaR:Automated Phylogenetic Sequence Cluster Identification from 'GenBank'

A pipeline for the identification, within taxonomic groups, of orthologous sequence clusters from 'GenBank' <https://www.ncbi.nlm.nih.gov/genbank/> as the first step in a phylogenetic analysis. The pipeline depends on a local alignment search tool and is, therefore, not dependent on differences in gene naming conventions and naming errors.

Maintained by Shixiang Wang. Last updated 8 months ago.

blastn genbank peer-reviewed phylogenetics sequence-alignment

23 stars 5.86 score 156 scripts

sylvainschmitt

rcontroll:Individual-Based Forest Growth Simulator 'TROLL'

'TROLL' is coded in C++ and it typically simulates hundreds of thousands of individuals over hundreds of years. The 'rcontroll' R package is a wrapper of 'TROLL'. 'rcontroll' includes functions that generate inputs for simulations and run simulations. Finally, it is possible to analyse the 'TROLL' outputs through tables, figures, and maps taking advantage of other R visualisation packages. 'rcontroll' also offers the possibility to generate a virtual LiDAR point cloud that corresponds to a snapshot of the simulated forest.

Maintained by Sylvain Schmitt. Last updated 6 months ago.

gsl cpp

6 stars 5.84 score 19 scripts

merck

gMCPLite:Lightweight Graph Based Multiple Comparison Procedures

A lightweight fork of 'gMCP' with functions for graphical described multiple test procedures introduced in Bretz et al. (2009) <doi:10.1002/sim.3495> and Bretz et al. (2011) <doi:10.1002/bimj.201000239>. Implements a flexible function using 'ggplot2' to create multiplicity graph visualizations. Contains instructions of multiplicity graph and graphical testing for group sequential design, described in Maurer and Bretz (2013) <doi:10.1080/19466315.2013.807748>, with necessary unit testing using 'testthat'.

Maintained by Nan Xiao. Last updated 1 years ago.

11 stars 5.79 score 14 scripts

bioc

qusage:qusage: Quantitative Set Analysis for Gene Expression

This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. The QuSAGE package also includes a mixed effects model implementation, as described in (Turner JA et al, BMC Bioinformatics, 2015), and a meta-analysis framework as described in (Meng H, et al. PLoS Comput Biol. 2019). For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)

Maintained by Christopher Bolen. Last updated 5 months ago.

genesetenrichment microarray rnaseq software immunooncology

5.65 score 185 scripts 1 dependents

bbuchsbaum

neuroim:Data Structures and Handling for Neuroimaging Data

A collection of data structures that represent volumetric brain imaging data. The focus is on basic data handling for 3D and 4D neuroimaging data. In addition, there are function to read and write NIFTI files and limited support for reading AFNI files.

Maintained by Bradley Buchsbaum. Last updated 4 years ago.

cpp

6 stars 5.64 score 48 scripts

graemeleehickey

bayesDP:Implementation of the Bayesian Discount Prior Approach for Clinical Trials

Functions for data augmentation using the Bayesian discount prior method for single arm and two-arm clinical trials, as described in Haddad et al. (2017) <doi:10.1080/10543406.2017.1300907>. The discount power prior methodology was developed in collaboration with the The Medical Device Innovation Consortium (MDIC) Computer Modeling & Simulation Working Group.

Maintained by Graeme L. Hickey. Last updated 3 months ago.

bayesian bayesian-inference bayesian-statistics clinical-trials mdic posterior-predictive posterior-probability prior-distribution openblas cpp

5.56 score 20 scripts 1 dependents

ssnn-airr

scoper:Spectral Clustering-Based Method for Identifying B Cell Clones

Provides a computational framework for identification of B cell clones from Adaptive Immune Receptor Repertoire sequencing (AIRR-Seq) data. Three main functions are included (identicalClones, hierarchicalClones, and spectralClones) that perform clustering among sequences of BCRs/IGs (B cell receptors/immunoglobulins) which share the same V gene, J gene and junction length. Nouri N and Kleinstein SH (2018) <doi: 10.1093/bioinformatics/bty235>. Nouri N and Kleinstein SH (2019) <doi: 10.1101/788620>. Gupta NT, et al. (2017) <doi: 10.4049/jimmunol.1601850>.

Maintained by Susanna Marquez. Last updated 3 months ago.

cpp

5.43 score 89 scripts

centerforstatistics-ugent

pim:Fit Probabilistic Index Models

Fit a probabilistic index model as described in Thas et al, 2012: <doi:10.1111/j.1467-9868.2011.01020.x>. The interface to the modeling function has changed in this new version. The old version is still available at R-Forge.

Maintained by Joris Meys. Last updated 3 months ago.

modelling statistics

10 stars 5.33 score 43 scripts

jaganmn

flint:Fast Library for Number Theory

An R interface to 'FLINT' <https://flintlib.org/>, a C library for number theory. 'FLINT' extends GNU 'MPFR' <https://www.mpfr.org/> and GNU 'MP' <https://gmplib.org/> with support for operations on standard rings (the integers, the integers modulo n, finite fields, the rational, p-adic, real, and complex numbers) as well as matrices and polynomials over rings. 'FLINT' implements midpoint-radius interval arithmetic, also known as ball arithmetic, in the real and complex numbers, enabling computation in arbitrary precision with rigorous propagation of rounding errors; see Johansson (2017) <doi:10.1109/TC.2017.2690633>. Finally, 'FLINT' provides ball arithmetic implementations of many special mathematical functions, with high coverage of reference works such as the NIST Digital Library of Mathematical Functions <https://dlmf.nist.gov/>. The R interface defines S4 classes, generic functions, and methods for representation and basic operations as well as plain R functions mirroring and vectorizing entry points in the C library.

Maintained by Mikael Jagan. Last updated 5 days ago.

flint mpfr4 gmp

5 stars 5.11 score 20 scripts

mclements

ascii:Export R Objects to Several Markup Languages

Coerce R object to 'asciidoc', 'txt2tags', 'restructuredText', 'org', 'textile' or 'pandoc' syntax. Package comes with a set of drivers for 'Sweave'.

Maintained by Mark Clements. Last updated 1 years ago.

8 stars 5.04 score 161 scripts 1 dependents

bioc

podkat:Position-Dependent Kernel Association Test

This package provides an association test that is capable of dealing with very rare and even private variants. This is accomplished by a kernel-based approach that takes the positions of the variants into account. The test can be used for pre-processed matrix data, but also directly for variant data stored in VCF files. Association testing can be performed whole-genome, whole-exome, or restricted to pre-defined regions of interest. The test is complemented by tools for analyzing and visualizing the results.

Maintained by Ulrich Bodenhofer. Last updated 5 months ago.

genetics wholegenome annotation variantannotation sequencing dataimport curl bzip2 xz-utils zlib cpp

5.02 score 6 scripts

evolutionary-optimization-laboratory

rmoo:Multi-Objective Optimization in R

The 'rmoo' package is a framework for multi- and many-objective optimization, which allows researchers and users versatility in parameter configuration, as well as tools for analysis, replication and visualization of results. The 'rmoo' package was built as a fork of the 'GA' package by Luca Scrucca(2017) <DOI:10.32614/RJ-2017-008> and implementing the Non-Dominated Sorting Genetic Algorithms proposed by K. Deb's.

Maintained by Francisco Benitez. Last updated 5 months ago.

metaheuristics multiobjective multiobjective-optimization nsga nsga2 nsga3 optimization pareto-front

30 stars 5.01 score 23 scripts

syksy

ePCR:Ensemble Penalized Cox Regression for Survival Prediction

The top-performing ensemble-based Penalized Cox Regression (ePCR) framework developed during the DREAM 9.5 mCRPC Prostate Cancer Challenge <https://www.synapse.org/ProstateCancerChallenge> presented in Guinney J, Wang T, Laajala TD, et al. (2017) <doi:10.1016/S1470-2045(16)30560-5> is provided here-in, together with the corresponding follow-up work. While initially aimed at modeling the most advanced stage of prostate cancer, metastatic Castration-Resistant Prostate Cancer (mCRPC), the modeling framework has subsequently been extended to cover also the non-metastatic form of advanced prostate cancer (CRPC). Readily fitted ensemble-based model S4-objects are provided, and a simulated example dataset based on a real-life cohort is provided from the Turku University Hospital, to illustrate the use of the package. Functionality of the ePCR methodology relies on constructing ensembles of strata in patient cohorts and averaging over them, with each ensemble member consisting of a highly optimized penalized/regularized Cox regression model. Various cross-validation and other modeling schema are provided for constructing novel model objects.

Maintained by Teemu Daniel Laajala. Last updated 1 years ago.

5.00 score 20 scripts

feiyoung

ILSE:Linear Regression Based on 'ILSE' for Missing Data

Linear regression when covariates include missing values by embedding the correlation information between covariates. Especially for block missing data, it works well. 'ILSE' conducts imputation and regression simultaneously and iteratively. More details can be referred to Huazhen Lin, Wei Liu and Wei Lan. (2021) <doi:10.1080/07350015.2019.1635486>.

Maintained by Wei Liu. Last updated 1 years ago.

fiml ilse linear-regression missing-data openblas cpp

2 stars 4.95 score 3 scripts

r-forge

VarSelLCM:Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values

Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.

Maintained by Mohammed Sedki. Last updated 6 years ago.

openblas cpp

4.95 score 49 scripts 2 dependents

kornl

Crossover:Analysis and Search of Crossover Designs

Generate and analyse crossover designs from combinatorial or search algorithms as well as from literature and a GUI to access them.

Maintained by Kornelius Rohmeyer. Last updated 1 years ago.

openblas cpp openjdk

6 stars 4.94 score 29 scripts

ralmond

RNetica:R interface to Netica(R) Bayesian Network Engine

This provides an R interface to the Netica (http://norsys.com/) Bayesian network library API.

Maintained by Russell Almond. Last updated 3 months ago.

bayesian-network

2 stars 4.92 score 14 scripts 2 dependents

bioc

MLSeq:Machine Learning Interface for RNA-Seq Data

This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART to RNA-Seq data.

Maintained by Gokmen Zararsiz. Last updated 5 months ago.

immunooncology sequencing rnaseq classification clustering

4.81 score 27 scripts 1 dependents

pchausse

momentfit:Methods of Moments

Several classes for moment-based models are defined. The classes are defined for moment conditions derived from a single equation or a system of equations. The conditions can also be expressed as functions or formulas. Several methods are also offered to facilitate the development of different estimation techniques. The methods that are currently provided are the Generalized method of moments (Hansen 1982; <doi:10.2307/1912775>), for single equations and systems of equation, and the Generalized Empirical Likelihood (Smith 1997; <doi:10.1111/j.0013-0133.1997.174.x>, Kitamura 1997; <doi:10.1214/aos/1069362388>, Newey and Smith 2004; <doi:10.1111/j.1468-0262.2004.00482.x>, and Anatolyev 2005 <doi:10.1111/j.1468-0262.2005.00601.x>).

Maintained by Pierre Chausse. Last updated 1 years ago.

fortran openblas

4.80 score 21 scripts 1 dependents

fatelarico

FinNet:Quickly Build and Manipulate Financial Networks

Providing classes, methods, and functions to deal with financial networks. Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'. Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network'). There are also ad-hoc functions for the Fiedler value, global network efficiency, and cascade-failure analysis.

Maintained by Fabio Ashtar Telarico. Last updated 5 months ago.

cpp

2 stars 4.78 score 7 scripts

tpetzoldt

simecol:Simulation of Ecological (and Other) Dynamic Systems

An object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. It supports structuring of simulation scenarios (to avoid copy and paste) and aims to improve readability and re-usability of code.

Maintained by Thomas Petzoldt. Last updated 8 months ago.

4.76 score 190 scripts

cdueben

cppcontainers:'C++' Standard Template Library Containers

Use 'C++' Standard Template Library containers interactively in R. Includes sets, unordered sets, multisets, unordered multisets, maps, unordered maps, multimaps, unordered multimaps, stacks, queues, priority queues, vectors, deques, forward lists, and lists.

Maintained by Christian Düben. Last updated 2 months ago.

cpp

4.70 score 1 scripts

yxlin

ggdmc:Cognitive Models

The package provides tools to fit the LBA, DDM, PM and 2-D diffusion models, using the population-based Markov Chain Monte Carlo.

Maintained by Yi-Shin Lin. Last updated 8 months ago.

openblas cpp

19 stars 4.66 score 24 scripts

guidoamoreira

bayesPO:Bayesian Inference for Presence-Only Data

Presence-Only data is best modelled with a Point Process Model. The work of Moreira and Gamerman (2022) <doi:10.1214/21-AOAS1569> provides a way to use exact Bayesian inference to model this type of data, which is implemented in this package.

Maintained by Guido Alberti Moreira. Last updated 5 months ago.

cpp openmp

3 stars 4.65 score 2 scripts

jpolzehl

aws:Adaptive Weights Smoothing

We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing, the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020). Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27. <doi:10.18637/jss.v095.i06>, Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2023), Magnetic Resonance Brain Imaging, 2nd Ed. Appendix A, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8>.

Maintained by Joerg Polzehl. Last updated 6 months ago.

fortran openblas openmp

4.61 score 38 scripts 8 dependents

brechtdv

prevalence:Tools for Prevalence Assessment Studies

The prevalence package provides Frequentist and Bayesian methods for prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available on the user's system. JAGS can be downloaded from <https://mcmc-jags.sourceforge.io/>.

Maintained by Brecht Devleesschauwer. Last updated 3 years ago.

jags cpp

2 stars 4.48 score 38 scripts

timginker

boiwsa:Seasonal Adjustment of Weekly Data

Perform seasonal adjustment of weekly data. The package provides a user-friendly interface for computing seasonally adjusted estimates of weekly data and includes functions for the creation of country-specific prior adjustment variables, as well as diagnostic tools to assess the quality of the adjustments. The method is described in more detail in Ginker (2023) <doi:10.13140/RG.2.2.12221.44000>.

Maintained by Tim Ginker. Last updated 2 months ago.

seasonal-adjustment seasonality time-series-analysis

4 stars 4.48 score 3 scripts

cran

NADA:Nondetects and Data Analysis for Environmental Data

Contains methods described by Dennis Helsel in his book "Nondetects And Data Analysis: Statistics for Censored Environmental Data".

Maintained by Lopaka Lee. Last updated 5 years ago.

2 stars 4.45 score 14 dependents

re2simlab

ViSiElse:A Visual Tool for Behavior Analysis over Time

A graphical R package designed to visualize behavioral observations over time. Based on raw time data extracted from video recorded sessions of experimental observations, ViSiElse grants a global overview of a process by combining the visualization of multiple actions timestamps for all participants in a single graph. Individuals and/or group behavior can easily be assessed. Supplementary features allow users to further inspect their data by adding summary statistics (mean, standard deviation, quantile or statistical test) and/or time constraints to assess the accuracy of the realized actions.

Maintained by Elodie Garnier. Last updated 5 years ago.

2 stars 4.34 score 11 scripts

bioc

ACME:Algorithms for Calculating Microarray Enrichment (ACME)

ACME (Algorithms for Calculating Microarray Enrichment) is a set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing "enrichment". It does not rely on a specific array technology (although the array should be a "tiling" array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.

Maintained by Sean Davis. Last updated 5 months ago.

technology microarray normalization

4.30 score 4 scripts

bioc

mogsa:Multiple omics data integrative clustering and gene set analysis

This package provide a method for doing gene set analysis based on multiple omics data.

Maintained by Chen Meng. Last updated 5 months ago.

geneexpression principalcomponent statisticalmethod clustering software

4.29 score 49 scripts

r-forge

distrSim:Simulation Classes Based on Package 'distr'

S4-classes for setting up a coherent framework for simulation within the distr family of packages.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

4.16 score 7 scripts 3 dependents

pepijn-devries

ProTrackR:Manipulate and Play 'ProTracker' Modules

'ProTracker' is a popular music tracker to sequence music on a Commodore Amiga machine. This package offers the opportunity to import, export, manipulate and play 'ProTracker' module files. Even though the file format could be considered archaic, it still remains popular to this date. This package intends to contribute to this popularity and therewith keeping the legacy of 'ProTracker' and the Commodore Amiga alive.

Maintained by Pepijn de Vries. Last updated 3 months ago.

4 stars 4.12 score 66 scripts

ecomets

saemix:Stochastic Approximation Expectation Maximization (SAEM) Algorithm

The 'saemix' package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm (i) computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, (ii) provides standard errors for the maximum likelihood estimator (iii) estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm (see Comets et al. (2017) <doi:10.18637/jss.v080.i03>). Many applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group. The full PDF documentation for the package including references about the algorithm and examples can be downloaded on the github of the IAME research institute for 'saemix': <https://github.com/iame-researchCenter/saemix/blob/7638e1b09ccb01cdff173068e01c266e906f76eb/docsaem.pdf>.

Maintained by Emmanuelle Comets. Last updated 1 years ago.

1 stars 4.07 score 165 scripts 6 dependents

choi-phd

maat:Multiple Administrations Adaptive Testing

Provides an extension of the shadow-test approach to computerized adaptive testing (CAT) implemented in the 'TestDesign' package for the assessment framework involving multiple tests administered periodically throughout the year. This framework is referred to as the Multiple Administrations Adaptive Testing (MAAT) and supports multiple item pools vertically scaled and multiple phases (stages) of CAT within each test. Between phases and tests, transitioning from one item pool (and associated constraints) to another is allowed as deemed necessary to enhance the quality of measurement.

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

4.00 score 5 scripts

kasselhingee

scorematchingad:Score Matching Estimation by Automatic Differentiation

Hyvärinen's score matching (Hyvärinen, 2005) <https://jmlr.org/papers/v6/hyvarinen05a.html> is a useful estimation technique when the normalising constant for a probability distribution is difficult to compute. This package implements score matching estimators using automatic differentiation in the 'CppAD' library <https://github.com/coin-or/CppAD> and is designed for quickly implementing score matching estimators for new models. Also available is general robustification (Windham, 1995) <https://www.jstor.org/stable/2346159>. Already in the package are estimators for directional distributions (Mardia, Kent and Laha, 2016) <doi:10.48550/arXiv.1604.08470> and the flexible Polynomially-Tilted Pairwise Interaction model for compositional data. The latter estimators perform well when there are zeros in the compositions (Scealy and Wood, 2023) <doi:10.1080/01621459.2021.2016422>, even many zeros (Scealy, Hingee, Kent, and Wood, 2024) <doi:10.1007/s11222-024-10412-w>. A partial interface to CppAD's ADFun objects is also available.

Maintained by Kassel Liam Hingee. Last updated 3 months ago.

automatic-differentiation score-matching statistical-inference cpp

3.98 score 1 scripts

clobatofern95

GPUmatrix:Basic Linear Algebra with GPU

GPUs are great resources for data analysis, especially in statistics and linear algebra. Unfortunately, very few packages connect R to the GPU, and none of them are transparent enough to run the computations on the GPU without substantial changes to the code. The maintenance of these packages is cumbersome: several of the earlier attempts have been removed from their respective repositories. It would be desirable to have a properly maintained R package that takes advantage of the GPU with minimal changes to the existing code. We have developed the GPUmatrix package (available on CRAN). GPUmatrix mimics the behavior of the Matrix package and extends R to use the GPU for computations. It includes single(FP32) and double(FP64) precision data types, and provides support for sparse matrices. It is easy to learn, and requires very few code changes to perform the operations on the GPU. GPUmatrix relies on either the Torch or Tensorflow R packages to perform the GPU operations. We have demonstrated its usefulness for several statistical applications and machine learning applications: non-negative matrix factorization, logistic regression and general linear models. We have also included a comparison of GPU and CPU performance on different matrix operations.

Maintained by Cesar Lobato-Fernandez. Last updated 1 years ago.

3.93 score 57 scripts 1 dependents

marcohlmann

metanetwork:Handling and Representing Trophic Networks in Space and Time

A toolbox to handle and represent trophic networks in space or time across aggregation levels. This package contains a layout algorithm specifically designed for trophic networks, using dimension reduction on a diffusion graph kernel and trophic levels. Importantly, this package provides a layout method applicable for large trophic networks. The package also implements network diversity indices at different aggregation levels and connectance computation.

Maintained by Marc Ohlmann. Last updated 2 years ago.

2 stars 3.89 score 77 scripts

wrathematics

kazaam:Tools for Tall Distributed Matrices

Many data science problems reduce to operations on very tall, skinny matrices. However, sometimes these matrices can be so tall that they are difficult to work with, or do not even fit into main memory. One strategy to deal with such objects is to distribute their rows across several processors. To this end, we offer an 'S4' class for tall, skinny, distributed matrices, called the 'shaq'. We also provide many useful numerical methods and statistics operations for operating on these distributed objects. The naming is a bit "tongue-in-cheek", with the class a play on the fact that 'Shaquille' 'ONeal' ('Shaq') is very tall, and he starred in the film 'Kazaam'.

Maintained by Drew Schmidt. Last updated 8 years ago.

openblas

3.82 score 133 scripts

reidt03

RadOnc:Analytical Tools for Radiation Oncology

Designed for the import, analysis, and visualization of dosimetric and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume histogram information from multiple treatment planning system platforms and 3D structural representations and dosimetric information from 'DICOM-RT' files. These tools also enable subsequent visualization and statistical analysis of these data.

Maintained by Reid F. Thompson. Last updated 2 months ago.

8 stars 3.78 score 19 scripts

bioc

LiquidAssociation:LiquidAssociation

The package contains functions for calculate direct and model-based estimators for liquid association. It also provides functions for testing the existence of liquid association given a gene triplet data.

Maintained by Yen-Yi Ho. Last updated 5 months ago.

pathways geneexpression cellbiology genetics network timecourse

3.78 score 3 scripts 1 dependents

bioc

lmdme:Linear Model decomposition for Designed Multivariate Experiments

linear ANOVA decomposition of Multivariate Designed Experiments implementation based on limma lmFit. Features: i)Flexible formula type interface, ii) Fast limma based implementation, iii) p-values for each estimated coefficient levels in each factor, iv) F values for factor effects and v) plotting functions for PCA and PLS.

Maintained by Cristobal Fresno. Last updated 5 months ago.

microarray onechannel twochannel visualization differentialexpression experimentdata cancer

3.78 score 1 scripts

guillaumeevin

GWEX:Multi-Site Stochastic Models for Daily Precipitation and Temperature

Application of multi-site models for daily precipitation and temperature data. This package is designed for an application to 105 precipitation and 26 temperature gauges located in Switzerland. It applies fitting procedures and provides weather generators described in the following references: - Evin, G., A.-C. Favre, and B. Hingray. (2018) <doi:10.5194/hess-22-655-2018>. - Evin, G., A.-C. Favre, and B. Hingray. (2018) <doi:10.1007/s00704-018-2404-x>.

Maintained by Guillaume Evin. Last updated 4 months ago.

cpp

2 stars 3.70 score 6 scripts

nicavan

dexisensitivity:'DEXi' Decision Tree Analysis and Visualization

Provides a versatile toolkit for analyzing and visualizing 'DEXi' (Decision EXpert for education) decision trees, facilitating multi-criteria decision analysis directly within R. Users can read .dxi files, manipulate decision trees, and evaluate various scenarios. It supports sensitivity analysis through Monte Carlo simulations, one-at-a-time approaches, and variance-based methods, helping to discern the impact of input variations. Additionally, it includes functionalities for generating sampling plans and an array of visualization options for decision trees and analysis results. A distinctive feature is the synoptic table plot, aiding in the efficient comparison of scenarios. Whether for in-depth decision modeling or sensitivity analysis, this package stands as a comprehensive solution. Definition of sensitivity analyses available in Carpani, Bergez and Monod (2012) <doi:10.1016/j.envsoft.2011.10.002> and detailed description of the package soon available in Alaphilippe, Allart, Carpani, Cavan, Monod and Bergez (submitted to Software Impacts).

Maintained by Nicolas Cavan. Last updated 5 months ago.

3.70 score

r-forge

distrTEst:Estimation and Testing Classes Based on Package 'distr'

Evaluation (S4-)classes based on package distr for evaluating procedures (estimators/tests) at data/simulation in a unified way.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

3.68 score 3 scripts 1 dependents

soroushmdg

gwid:Genome-Wide Identity-by-Descent

Methods and tools for the analysis of Genome Wide Identity-by-Descent ('gwid') mapping data, focusing on testing whether there is a higher occurrence of Identity-By-Descent (IBD) segments around potential causal variants in cases compared to controls, which is crucial for identifying rare variants. To enhance its analytical power, 'gwid' incorporates a Sliding Window Approach, allowing for the detection and analysis of signals from multiple Single Nucleotide Polymorphisms (SNPs).

Maintained by Soroush Mahmoudiandehkordi. Last updated 7 months ago.

1 stars 3.60 score 4 scripts

r-forge

PST:Probabilistic Suffix Trees and Variable Length Markov Chains

Provides a framework for analysing state sequences with probabilistic suffix trees (PST), the construction that stores variable length Markov chains (VLMC). Besides functions for learning and optimizing VLMC models, the PST library includes many additional tools to analyse sequence data with these models: visualization tools, functions for sequence prediction and artificial sequences generation, as well as for context and pattern mining. The package is specifically adapted to the field of social sciences by allowing to learn VLMC models from sets of individual sequences possibly containing missing values, and by accounting for case weights. The library also allows to compute probabilistic divergence between two models, and to fit segmented VLMC, where sub-models fitted to distinct strata of the learning sample are stored in a single PST. This software results from research work executed within the framework of the Swiss National Centre of Competence in Research LIVES, which is financed by the Swiss National Science Foundation. The authors are grateful to the Swiss National Science Foundation for its financial support.

Maintained by Alexis Gabadinho. Last updated 4 years ago.

3.56 score 36 scripts

fhollenbach

EBMAforecast:Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms

Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in this package are Montgomery, Hollenbach, and Ward (2015) <doi:10.1016/j.ijforecast.2014.08.001> and Montgomery, Hollenbach, and Ward (2012) <doi:10.1093/pan/mps002>.

Maintained by Florian M. Hollenbach. Last updated 1 years ago.

cpp

2 stars 3.56 score 12 scripts 1 dependents

sth1402

DynTxRegime:Methods for Estimating Optimal Dynamic Treatment Regimes

Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Maintained by Shannon T. Holloway. Last updated 1 years ago.

2 stars 3.44 score 115 scripts 2 dependents

mechantrouquin

landsepi:Landscape Epidemiology and Evolution

A stochastic, spatially-explicit, demo-genetic model simulating the spread and evolution of a plant pathogen in a heterogeneous landscape to assess resistance deployment strategies. It is based on a spatial geometry for describing the landscape and allocation of different cultivars, a dispersal kernel for the dissemination of the pathogen, and a SEIR ('Susceptible-Exposed-Infectious-Removed’) structure with a discrete time step. It provides a useful tool to assess the performance of a wide range of deployment options with respect to their epidemiological, evolutionary and economic outcomes. Loup Rimbaud, Julien Papaïx, Jean-François Rey, Luke G Barrett, Peter H Thrall (2018) <doi:10.1371/journal.pcbi.1006067>.

Maintained by Jean-François Rey. Last updated 6 months ago.

gsl cpp

3.40 score 18 scripts

sth1402

modelObj:A Model Object Framework for Regression Analysis

A utility library to facilitate the generalization of statistical methods built on a regression framework. Package developers can use 'modelObj' methods to initiate a regression analysis without concern for the details of the regression model and the method to be used to obtain parameter estimates. The specifics of the regression step are left to the user to define when calling the function. The user of a function developed within the 'modelObj' framework creates as input a 'modelObj' that contains the model and the R methods to be used to obtain parameter estimates and to obtain predictions. In this way, a user can easily go from linear to non-linear models within the same package.

Maintained by Shannon T. Holloway. Last updated 3 years ago.

3.32 score 23 scripts 3 dependents

bernhard-da

sdcTable:Methods for Statistical Disclosure Control in Tabular Data

Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression as described for example in Hundepol et al. (2012) <doi:10.1002/9781118348239> are covered in this package.

Maintained by Bernhard Meindl. Last updated 18 days ago.

glpk cpp

1 stars 3.32 score 25 scripts 2 dependents

bioc

mosaics:MOSAiCS (MOdel-based one and two Sample Analysis and Inference for ChIP-Seq)

This package provides functions for fitting MOSAiCS and MOSAiCS-HMM, a statistical framework to analyze one-sample or two-sample ChIP-seq data of transcription factor binding and histone modification.

Maintained by Dongjun Chung. Last updated 5 months ago.

chipseq sequencing transcription genetics bioinformatics cpp

3.30 score 8 scripts

bioc

diggit:Inference of Genetic Variants Driving Cellular Phenotypes

Inference of Genetic Variants Driving Cellullar Phenotypes by the DIGGIT algorithm

Maintained by Mariano J Alvarez. Last updated 5 months ago.

systemsbiology networkenrichment geneexpression functionalprediction generegulation

3.30 score 3 scripts

villegar

scrappy:A Simple Web Scraper

A group of functions to scrape data from different websites, for academic purposes.

Maintained by Roberto Villegas-Diaz. Last updated 1 years ago.

4 stars 3.30 score

joblion

MixAll:Clustering and Classification using Model-Based Mixture Models

Algorithms and methods for model-based clustering and classification. It supports various types of data: continuous, categorical and counting and can handle mixed data of these types. It can fit Gaussian (with diagonal covariance structure), gamma, categorical and Poisson models. The algorithms also support missing values.

Maintained by Serge Iovleff. Last updated 11 months ago.

cpp openmp

3.29 score 97 scripts

wojtacht

hmsr:Multipopulation Evolutionary Strategy HMS

The HMS (Hierarchic Memetic Strategy) is a composite global optimization strategy consisting of a multi-population evolutionary strategy and some auxiliary methods. The HMS makes use of a dynamically-evolving data structure that provides an organization among the component populations. It is a tree with a fixed maximal height and variable internal node degree. Each component population is governed by a particular evolutionary engine. This package provides a simple R implementation with examples of using different genetic algorithms as the population engines. References: J. Sawicki, M. Łoś, M. Smołka, J. Alvarez-Aramberri (2022) <doi:10.1007/s11047-020-09836-w>.

Maintained by Wojciech Achtelik. Last updated 1 years ago.

3 stars 3.18 score 5 scripts

jchiquet

quadrupen:Sparsity by Worst-Case Quadratic Penalties

Fits classical sparse regression models with efficient active set algorithms by solving quadratic problems as described by Grandvalet, Chiquet and Ambroise (2017) <doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).

Maintained by Julien Chiquet. Last updated 9 months ago.

openblas cpp

3.18 score 30 scripts

r-forge

pems.utils:Portable Emissions (and Other Mobile) Measurement System Utilities

Utility functions for the handling, analysis and visualisation of data from portable emissions measurement systems ('PEMS') and other similar mobile activity monitoring devices. The package includes a dedicated 'pems' data class that manages many of the quality control, unit handling and data archiving issues that can hinder efforts to standardise 'PEMS' research.

Maintained by Karl Ropkins. Last updated 3 months ago.

openjdk

3.06 score 19 scripts

thomascjohnson

quietR:Simplify Output Verbosity

Simplifies output suppression logic in R packages, as it's common to develop some form of it in R. 'quietR' intends to simplify that problem and allow a set of simple toggle functions to be used to suppress console output.

Maintained by Thomas Johnson. Last updated 6 years ago.

2 stars 3.00 score 1 scripts

newmi1988

seeds:Estimate Hidden Inputs using the Dynamic Elastic Net

Algorithms to calculate the hidden inputs of systems of differential equations. These hidden inputs can be interpreted as a control that tries to minimize the discrepancies between a given model and taken measurements. The idea is also called the Dynamic Elastic Net, as proposed in the paper "Learning (from) the errors of a systems biology model" (Engelhardt, Froelich, Kschischo 2016) <doi:10.1038/srep20772>. To use the experimental SBML import function, the 'rsbml' package is required. For installation I refer to the official 'rsbml' page: <https://bioconductor.org/packages/release/bioc/html/rsbml.html>.

Maintained by Tobias Newmiwaka. Last updated 4 years ago.

3.00 score 2 scripts

bioc

Rtreemix:Rtreemix: Mutagenetic trees mixture models.

Rtreemix is a package that offers an environment for estimating the mutagenetic trees mixture models from cross-sectional data and using them for various predictions. It includes functions for fitting the trees mixture models, likelihood computations, model comparisons, waiting time estimations, stability analysis, etc.

Maintained by Jasmina Bogojeska. Last updated 1 months ago.

statisticalmethod cpp

2.86 score 12 scripts

jpison

GAparsimony:Searching Parsimony Models with Genetic Algorithms

Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) <DOI:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.

Maintained by F.J. Martinez-de-Pison. Last updated 2 years ago.

6 stars 2.78 score 9 scripts

steppdev

stepp:Subpopulation Treatment Effect Pattern Plot (STEPP)

A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two or more treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group.

Maintained by Wai-ki Yip. Last updated 8 months ago.

fortran

2.75 score 28 scripts

guidoamoreira

pompp:Presence-Only for Marked Point Process

Inspired by Moreira and Gamerman (2022) <doi:10.1214/21-AOAS1569>, this methodology expands the idea by including Marks in the point process. Using efficient 'C++' code, the estimation is possible and made faster with 'OpenMP' <https://www.openmp.org/> enabled computers. This package was developed under the project PTDC/MAT-STA/28243/2017, supported by Portuguese funds through the Portuguese Foundation for Science and Technology (FCT).

Maintained by Guido Alberti Moreira. Last updated 2 years ago.

cpp openmp

2.70 score

mnwright

bnnSurvival:Bagged k-Nearest Neighbors Survival Prediction

Implements a bootstrap aggregated (bagged) version of the k-nearest neighbors survival probability prediction method (Lowsky et al. 2013). In addition to the bootstrapping of training samples, the features can be subsampled in each baselearner to break the correlation between them. The Rcpp package is used to speed up the computation.

Maintained by Marvin N. Wright. Last updated 8 years ago.

cpp

1 stars 2.70 score 5 scripts

jleydold

rstream:Streams of Random Numbers

Unified object oriented interface for multiple independent streams of random numbers from different sources.

Maintained by Josef Leydold. Last updated 2 years ago.

2.69 score 54 scripts 3 dependents

cran

capushe:CAlibrating Penalities Using Slope HEuristics

Calibration of penalized criteria for model selection. The calibration methods available are based on the slope heuristics.

Maintained by Vincent Brault. Last updated 1 years ago.

2.65 score 15 dependents

hkestler

BiTrinA:Binarization and Trinarization of One-Dimensional Data

Provides methods for the binarization and trinarization of one-dimensional data and some visualization functions.

Maintained by Hans Kestler. Last updated 1 years ago.

2.52 score 33 scripts

svizcaya

gems:Generalized Multistate Simulation Model

Simulate and analyze multistate models with general hazard functions. gems provides functionality for the preparation of hazard functions and parameters, simulation from a general multistate model and predicting future events. The multistate model is not required to be a Markov model and may take the history of previous events into account. In the basic version, it allows to simulate from transition-specific hazard function, whose parameters are multivariable normally distributed.

Maintained by Luisa Salazar Vizcaya. Last updated 8 years ago.

2.52 score 33 scripts

hkestler

Binarize:Binarization of One-Dimensional Data

Provides methods for the binarization of one-dimensional data and some visualization functions.

Maintained by Hans Kestler. Last updated 2 years ago.

1 stars 2.48 score 9 scripts

cedricbriandgithub

stacomiR:Fish Migration Monitoring

Graphical outputs and treatment for a database of fish pass monitoring. It is a part of the 'STACOMI' open source project developed in France by the French Office for Biodiversity institute to centralize data obtained by fish pass monitoring. This version is available in French and English. See <http://stacomir.r-forge.r-project.org/> for more information on 'STACOMI'.

Maintained by Cedric Briand. Last updated 1 years ago.

1 stars 2.43 score 27 scripts

fbertran

robustfa:Object Oriented Solution for Robust Factor Analysis

Outliers virtually exist in any datasets of any application field. To avoid the impact of outliers, we need to use robust estimators. Classical estimators of multivariate mean and covariance matrix are the sample mean and the sample covariance matrix. Outliers will affect the sample mean and the sample covariance matrix, and thus they will affect the classical factor analysis which depends on the classical estimators (Pison, G., Rousseeuw, P.J., Filzmoser, P. and Croux, C. (2003) <doi:10.1016/S0047-259X(02)00007-6>). So it is necessary to use the robust estimators of the sample mean and the sample covariance matrix. There are several robust estimators in the literature: Minimum Covariance Determinant estimator, Orthogonalized Gnanadesikan-Kettenring, Minimum Volume Ellipsoid, M, S, and Stahel-Donoho. The most direct way to make multivariate analysis more robust is to replace the sample mean and the sample covariance matrix of the classical estimators to robust estimators (Maronna, R.A., Martin, D. and Yohai, V. (2006) <doi:10.1002/0470010940>) (Todorov, V. and Filzmoser, P. (2009) <doi:10.18637/jss.v032.i03>), which is our choice of robust factor analysis. We created an object oriented solution for robust factor analysis based on new S4 classes.

Maintained by Frederic Bertrand. Last updated 2 years ago.

2.40 score 25 scripts

ktabelow

dti:Analysis of Diffusion Weighted Imaging (DWI) Data

Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data. The functionality includes diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), modeling for high angular resolution diffusion weighted imaging (HARDI) using Q-ball-reconstruction and tensor mixture models, several methods for structural adaptive smoothing including POAS and msPOAS, and a streamline fiber tracking for tensor and tensor mixture models. The package provides functionality to manipulate and visualize results in 2D and 3D.

Maintained by Karsten Tabelow. Last updated 6 months ago.

fortran openblas cpp

2.20 score 16 scripts

yusenzhang

qkerntool:Q-Kernel-Based and Conditionally Negative Definite Kernel-Based Machine Learning Tools

Nonlinear machine learning tool for classification, clustering and dimensionality reduction. It integrates 12 q-kernel functions and 15 conditional negative definite kernel functions and includes the q-kernel and conditional negative definite kernel version of density-based spatial clustering of applications with noise, spectral clustering, generalized discriminant analysis, principal component analysis, multidimensional scaling, locally linear embedding, sammon's mapping and t-Distributed stochastic neighbor embedding.

Maintained by Yusen Zhang. Last updated 6 years ago.

1 stars 2.19 score 31 scripts

maikol-solis

sobolnp:Nonparametric Sobol Estimator with Bootstrap Bandwidth

Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias. The package is based on the paper Solís, M. (2018) <arXiv:1803.03333>.

Maintained by Maikol Solís. Last updated 2 years ago.

bandwidth bootstrap cross-validation nonparametric-regression sensitivity-analysis

2.00 score 1 scripts

davidsleonard

leiv:Bivariate Linear Errors-In-Variables Estimation

Estimate the slope and intercept of a bivariate linear relationship by calculating a posterior density that is invariant to interchange and scaling of the coordinates.

Maintained by David Leonard. Last updated 10 years ago.

2.00 score 3 scripts

lionning

MuChPoint:Multiple Change Point

Nonparametric approach to estimate the location of block boundaries (change-points) of non-overlapping blocks in a random symmetric matrix which consists of random variables whose distribution changes from block to block. BRAULT Vincent, OUADAH Sarah, SANSONNET Laure and LEVY-LEDUC Celine (2017) <doi:10.1016/j.jmva.2017.12.005>.

Maintained by Brault Vincent. Last updated 3 years ago.

cpp

2.00 score 3 scripts

cran

Ease:Simulating Explicit Population Genetics Models

Implementation in a simple and efficient way of fully customisable population genetics simulations, considering multiple loci that have epistatic interactions. Specifically suited to the modelling of multilocus nucleocytoplasmic systems (with both diploid and haploid loci), it is nevertheless possible to simulate purely diploid (or purely haploid) genetic models. Examples of models that can be simulated with Ease are numerous, for example models of genetic incompatibilities as presented by Marie-Orleach et al. (2022) <doi:10.1101/2022.07.25.501356>. Many others are conceivable, although few are actually explored, Ease having been developed in particular to provide a solution so that these kinds of models can be simulated simply.

Maintained by Ehouarn Le Faou. Last updated 2 years ago.

cpp

2.00 score

cran

NiLeDAM:Monazite Dating for the NiLeDAM Team

Th-U-Pb electron microprobe age dating of monazite, as originally described in <doi:10.1016/0009-2541(96)00024-1>.

Maintained by Nathalie Vialaneix. Last updated 2 years ago.

2.00 score

cran

redcas:An Interface to the Computer Algebra System 'REDUCE'

'REDUCE' is a portable general-purpose computer algebra system supporting scalar, vector, matrix and tensor algebra, symbolic differential and integral calculus, arbitrary precision numerical calculations and output in 'LaTeX' format. 'REDUCE' is based on 'Lisp' and is available on the two dialects 'Portable Standard Lisp' ('PSL') and 'Codemist Standard Lisp' ('CSL'). The 'redcas' package provides an interface for executing arbitrary 'REDUCE' code interactively from 'R', returning output as character vectors. 'R' code and 'REDUCE' code can be interspersed. It also provides a specialized function for calling the 'REDUCE' feature for solving systems of equations, returning the output as an 'R' object designed for the purpose. A further specialized function uses 'REDUCE' features to generate 'LaTeX' output and post-processes this for direct use in 'LaTeX' documents, e.g. using 'Sweave'.

Maintained by Martin Gregory. Last updated 5 months ago.

1.70 score

cran

mixedsde:Estimation Methods for Stochastic Differential Mixed Effects Models

Inference on stochastic differential models Ornstein-Uhlenbeck or Cox-Ingersoll-Ross, with one or two random effects in the drift function.

Maintained by Charlotte Dion. Last updated 6 years ago.

1.70 score

cran

crops:Changepoints for a Range of Penalties (CROPS)

Implements the Changepoints for a Range of Penalties (CROPS) algorithm of Haynes et al. (2017) <doi:10.1080/10618600.2015.1116445> for finding all of the optimal segmentations for multiple penalty values over a continuous range.

Maintained by Daniel Grose. Last updated 3 years ago.

1.48 score 1 dependents

cran

truncSP:Semi-parametric estimators of truncated regression models

Semi-parametric estimation of truncated linear regression models

Maintained by Anita Lindmark. Last updated 11 years ago.

1.48 score 1 dependents

cran

swash:Swash-Backwash Model for the Single Epidemic Wave

The Swash-Backwash Model for the Single Epidemic Wave was developed by Cliff and Haggett (2006) <doi:10.1007/s10109-006-0027-8> to model the velocity of spread of infectious diseases across space. This package enables the calculation of the Swash-Backwash Model for user-supplied panel data on regional infections. The package also provides additional functions for bootstrap confidence intervals, country comparison, visualization of results, and data management.

Maintained by Thomas Wieland. Last updated 1 months ago.

1.30 score

cran

MSigSeg:Multiple SIGnal SEGmentation

Traditional methods typically detect breakpoints from individual signals, which means that when applied separately to multiple signals, the breakpoints are not aligned. However, this package implements a common breakpoint detection approach for multiple piecewise constant signals, resulting in increased detection sensitivity and specificity. By employing various techniques, optimal performance is ensured, and computation is accelerated. We hope that this package will be beneficial for researchers in signal processing, bioinformatics, economy, and other related fields. The segmentation(), lambda_estimator() functions are the main functions of this package.

Maintained by Xuanyu Liu. Last updated 1 years ago.

1.00 score

cran

ltable:Easy to Make (Lazy) Tables

Constructs tables of counts and proportions out of data sets with possibility to insert tables to Excel, Word, HTML, and PDF documents. Transforms tables to data suitable for modelling. Features Gibbs sampling based log-linear (NB2) and power analyses (original by Oleksandr Ocheredko <doi:10.35566/isdsa2019c5>) for tabulated data.

Maintained by Ocheredko Oleksandr. Last updated 9 months ago.

1.00 score

nassimzbalah

IOLS:Iterated Ordinary Least Squares Regression

Addresses the 'log of zero' by developing a new family of estimators called iterated Ordinary Least Squares. This family nests standard approaches such as log-linear and Poisson regressions, offers several computational advantages, and corresponds to the correct way to perform the popular log(Y + 1) transformation. For more details about how to use it, see the notebook at: <https://www.davidbenatia.com/>.

Maintained by Nassim Zbalah. Last updated 2 years ago.

1.00 score

jchiquet

spinyReg:Sparse Generative Model and Its EM Algorithm

Implements a generative model that uses a spike-and-slab like prior distribution obtained by multiplying a deterministic binary vector. Such a model allows an EM algorithm, optimizing a type-II log-likelihood.

Maintained by Julien Chiquet. Last updated 10 years ago.

1.00 score 1 scripts

masedki

MvBinary:Modelling Multivariate Binary Data with Blocks of Specific One-Factor Distribution

Modelling Multivariate Binary Data with Blocks of Specific One-Factor Distribution. Variables are grouped into independent blocks. Each variable is described by two continuous parameters (its marginal probability and its dependency strength with the other block variables), and one binary parameter (positive or negative dependency). Model selection consists in the estimation of the repartition of the variables into blocks. It is carried out by the maximization of the BIC criterion by a deterministic (faster) algorithm or by a stochastic (more time consuming but optimal) algorithm. Tool functions facilitate the model interpretation.

Maintained by Mohammed Sedki. Last updated 8 years ago.

1.00 score 5 scripts

sth1402

ICODS:Data Analysis for ODS and Case-Cohort Designs with Interval-Censoring

Sieve semiparametric likelihood methods for analyzing interval-censored failure time data from an outcome-dependent sampling (ODS) design and from a case-cohort design. Zhou, Q., Cai, J., and Zhou, H. (2018) <doi:10.1111/biom.12744>; Zhou, Q., Zhou, H., and Cai, J. (2017) <doi:10.1093/biomet/asw067>.

Maintained by Shannon T. Holloway. Last updated 3 years ago.

1.00 score

sth1402

dtrSurv:Dynamic Treatment Regimes for Survival Analysis

Provides methods for estimating multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring. Cho, H., Holloway, S. T., and Kosorok, M. R. (2020) <arXiv:2012.03294>.

Maintained by Shannon T. Holloway. Last updated 3 years ago.

fortran

1.00 score 9 scripts

murattinic

InfoTrad:Calculates the Probability of Informed Trading (PIN)

Estimates the probability of informed trading (PIN) initially introduced by Easley et. al. (1996) <doi:10.1111/j.1540-6261.1996.tb04074.x> . Contribution of the package is that it uses likelihood factorizations of Easley et. al. (2010) <doi:10.1017/S0022109010000074> (EHO factorization) and Lin and Ke (2011) <doi:10.1016/j.finmar.2011.03.001> (LK factorization). Moreover, the package uses different estimation algorithms. Specifically, the grid-search algorithm proposed by Yan and Zhang (2012) <doi:10.1016/j.jbankfin.2011.08.003> , hierarchical agglomerative clustering approach proposed by Gan et. al. (2015) <doi:10.1080/14697688.2015.1023336> and later extended by Ersan and Alici (2016) <doi:10.1016/j.intfin.2016.04.001> .

Maintained by Murat Tinic. Last updated 8 years ago.

1.00 score 9 scripts

cran

bikm1:Co-Clustering Adjusted Rand Index and Bikm1 Procedure for Contingency and Binary Data-Sets

Co-clustering of the rows and columns of a contingency or binary matrix, or double binary matrices and model selection for the number of row and column clusters. Three models are considered: the Poisson latent block model for contingency matrix, the binary latent block model for binary matrix and a new model we develop: the multiple latent block model for double binary matrices. A new procedure named bikm1 is implemented to investigate more efficiently the grid of numbers of clusters. Then, the studied model selection criteria are the integrated completed likelihood (ICL) and the Bayesian integrated likelihood (BIC). Finally, the co-clustering adjusted Rand index (CARI) to measure agreement between co-clustering partitions is implemented. Robert Valerie, Vasseur Yann, Brault Vincent (2021) <doi:10.1007/s00357-020-09379-w>.

Maintained by Valerie Robert. Last updated 4 years ago.

1 stars 1.00 score

cran

HCT:Calculates Significance Criteria and Power for a Single Arm Trial

Given a database of previous treatment/placebo estimates, their standard errors and sample sizes, the program calculates a significance criteria and power estimate that takes into account the among trial variation.

Maintained by David A. Schoenfeld. Last updated 3 years ago.

1.00 score

cran

SPB:Simple Progress Bars for Procedural Coding

Provides a simple progress bar to use for basic and advanced users that suits all those who prefer procedural programming. It is especially useful for integration into markdown files thanks to the progress bar's customisable appearance.

Maintained by Fabio Ashtar Telarico. Last updated 3 years ago.

1.00 score

sth1402

ChangepointTesting:Change Point Estimation for Clustered Signals

A multiple testing procedure for clustered alternative hypotheses. It is assumed that the p-values under the null hypotheses follow U(0,1) and that the distributions of p-values from the alternative hypotheses are stochastically smaller than U(0,1). By aggregating information, this method is more sensitive to detecting signals of low magnitude than standard methods. Additionally, sporadic small p-values appearing within a null hypotheses sequence are avoided by averaging on the neighboring p-values.

Maintained by Shannon T. Holloway. Last updated 3 years ago.

1.00 score 2 scripts

cran

MCBackscattering:Monte Carlo Simulation for Surface Backscattering

Monte Carlo simulation is a stochastic method computing trajectories of photons in media. Surface backscattering is performing calculations in semi-infinite media and summarizing photon flux leaving the surface. This simulation is modeling the optical measurement of diffuse reflectance using an incident light beam. The semi-infinite media is considered to have flat surface. Media, typically biological tissue, is described by four optical parameters: absorption coefficient, scattering coefficient, anisotropy factor, refractive index. The media is assumed to be homogeneous. Computational parameters of the simulation include: number of photons, radius of incident light beam, lowest photon energy threshold, intensity profile (halo) radius, spatial resolution of intensity profile. You can find more information and validation in the Open Access paper. Laszlo Baranyai (2020) <doi:10.1016/j.mex.2020.100958>.

Maintained by Laszlo Baranyai. Last updated 5 years ago.

1.00 score