R-universe search: needs:rgl

r-lidar

lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.

Maintained by Jean-Romain Roussel. Last updated 2 months ago.

als forestry las laz lidar point-cloud remote-sensing openblas cpp openmp

623 stars 14.47 score 844 scripts 8 dependents

bioc

mixOmics:Omics Data Integration Project

Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.

Maintained by Eva Hamrud. Last updated 2 days ago.

immunooncology microarray sequencing metabolomics metagenomics proteomics geneprediction multiplecomparison classification regression bioconductor genomics genomics-data genomics-visualization multivariate-analysis multivariate-statistics omics r-pkg r-project

185 stars 13.75 score 1.3k scripts 22 dependents

friendly

matlib:Matrix Functions for Teaching and Learning Linear Algebra and Multivariate Statistics

A collection of matrix functions for teaching and learning matrix linear algebra as used in multivariate statistical methods. Many of these functions are designed for tutorial purposes in learning matrix algebra ideas using R. In some cases, functions are provided for concepts available elsewhere in R, but where the function call or name is not obvious. In other cases, functions are provided to show or demonstrate an algorithm. In addition, a collection of functions are provided for drawing vector diagrams in 2D and 3D and for rendering matrix expressions and equations in LaTeX.

Maintained by Michael Friendly. Last updated 15 days ago.

diagrams linear-equations matrix matrix-functions matrix-visualizer vector vignette

65 stars 12.89 score 900 scripts 11 dependents

geomorphr

geomorph:Geometric Morphometric Analyses of 2D and 3D Landmark Data

Read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform shape analyses, and provide graphical depictions of shapes and patterns of shape variation.

Maintained by Dean Adams. Last updated 2 months ago.

76 stars 12.05 score 700 scripts 6 dependents

friendly

heplots:Visualizing Hypothesis Tests in Multivariate Linear Models

Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.

Maintained by Michael Friendly. Last updated 6 days ago.

linear-hypotheses matrices multivariate-linear-models plot repeated-measure-designs visualizing-hypothesis-tests

9 stars 11.78 score 1.1k scripts 7 dependents

tylermorganwall

rayshader:Create Maps and Visualize Data in 2D and 3D

Uses a combination of raytracing and multiple hill shading methods to produce 2D and 3D data visualizations and maps. Includes water detection and layering functions, programmable color palette generation, several built-in textures for hill shading, 2D and 3D plotting options, a built-in path tracer, 'Wavefront' OBJ file export, and the ability to save 3D visualizations to a 3D printable format.

Maintained by Tyler Morgan-Wall. Last updated 2 months ago.

cpp

2.1k stars 11.51 score 1.5k scripts 5 dependents

ovvo-financial

NNS:Nonlinear Nonparametric Statistics

Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).

Maintained by Fred Viole. Last updated 2 days ago.

clustering econometrics machine-learning nonlinear nonparametric partial-moments statistics time-series cpp

72 stars 10.77 score 66 scripts 3 dependents

zarquon42b

Morpho:Calculations and Visualisations Related to Geometric Morphometrics

A toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.

Maintained by Stefan Schlager. Last updated 5 months ago.

openblas cpp openmp

51 stars 10.01 score 218 scripts 13 dependents

natverse

nat:NeuroAnatomy Toolbox for Analysis of 3D Image Data

NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D biological image data, especially traced neurons. Reads and writes 3D images in NRRD and 'Amira' AmiraMesh formats and reads surfaces in 'Amira' hxsurf format. Traced neurons can be imported from and written to SWC and 'Amira' LineSet and SkeletonGraph formats. These data can then be visualised in 3D via 'rgl', manipulated including applying calculated registrations, e.g. using the 'CMTK' registration suite, and analysed. There is also a simple representation for neurons that have been subjected to 3D skeletonisation but not formally traced; this allows morphological comparison between neurons including searches and clustering (via the 'nat.nblast' extension package).

Maintained by Gregory Jefferis. Last updated 6 months ago.

3d connectomics image-analysis neuroanatomy neuroanatomy-toolbox neuron neuron-morphology neuroscience visualisation

67 stars 9.94 score 436 scripts 2 dependents

friendly

candisc:Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

Functions for computing and visualizing generalized canonical discriminant analyses and canonical correlation analysis for a multivariate linear model. Traditional canonical discriminant analysis is restricted to a one-way 'MANOVA' design and is equivalent to canonical correlation analysis between a set of quantitative response variables and a set of dummy variables coded from the factor variable. The 'candisc' package generalizes this to higher-way 'MANOVA' designs for all factors in a multivariate linear model, computing canonical scores and vectors for each term. The graphic functions provide low-rank (1D, 2D, 3D) visualizations of terms in an 'mlm' via the 'plot.candisc' and 'heplot.candisc' methods. Related plots are now provided for canonical correlation analysis when all predictors are quantitative.

Maintained by Michael Friendly. Last updated 2 days ago.

dimension-reduction multivariate-linear-models visualization

15 stars 8.99 score 221 scripts 3 dependents

mandymejia

ciftiTools:Tools for Reading, Writing, Viewing and Manipulating CIFTI Files

CIFTI files contain brain imaging data in "grayordinates," which represent the gray matter as cortical surface vertices (left and right) and subcortical voxels (cerebellum, basal ganglia, and other deep gray matter). 'ciftiTools' provides a unified environment for reading, writing, visualizing and manipulating CIFTI-format data. It supports the "dscalar," "dlabel," and "dtseries" intents. Grayordinate data is read in as a "xifti" object, which is structured for convenient access to the data and metadata, and includes support for surface geometry files to enable spatially-dependent functionality such as static or interactive visualizations and smoothing.

Maintained by Amanda Mejia. Last updated 2 months ago.

47 stars 8.90 score 176 scripts 4 dependents

iandryden

shapes:Statistical Shape Analysis

Routines for the statistical analysis of landmark shapes, including Procrustes analysis, graphical displays, principal components analysis, permutation and bootstrap tests, thin-plate spline transformation grids and comparing covariance matrices. See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, with Applications in R (2nd Edition), John Wiley and Sons.

Maintained by Ian Dryden. Last updated 3 days ago.

7 stars 8.61 score 225 scripts 24 dependents

kisungyou

Rdimtools:Dimension Reduction and Estimation Methods

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

Maintained by Kisung You. Last updated 2 years ago.

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

52 stars 8.37 score 186 scripts 8 dependents

bioc

POMA:Tools for Omics Data Analysis

The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.

Maintained by Pol Castellano-Escuder. Last updated 4 months ago.

batcheffect classification clustering decisiontree dimensionreduction multidimensionalscaling normalization preprocessing principalcomponent regression rnaseq software statisticalmethod visualization bioconductor bioinformatics data-visualization dimension-reduction exploratory-data-analysis machine-learning omics-data-integration pipeline pre-processing statistical-analysis user-friendly workflow

11 stars 8.16 score 20 scripts 1 dependents

relund

gMOIP:Tools for 2D and 3D Plots of Single and Multi-Objective Linear/Integer Programming Models

Make 2D and 3D plots of linear programming (LP), integer linear programming (ILP), or mixed integer linear programming (MILP) models with up to three objectives. Plots of both the solution and criterion space are possible. For instance the non-dominated (Pareto) set for bi-objective LP/ILP/MILP programming models (see vignettes for an overview). The package also contains an function for checking if a point is inside the convex hull.

Maintained by Lars Relund Nielsen. Last updated 5 months ago.

2d-plot 3d-plot bi-objective convex-hull integer-programming linear-programming math milp mixed-integer-programming multi-objective polytope tri-objective visualization

5 stars 7.81 score 79 scripts 3 dependents

bioc

AlpsNMR:Automated spectraL Processing System for NMR

Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.

Maintained by Sergio Oller Moreno. Last updated 5 months ago.

software preprocessing visualization classification cheminformatics metabolomics dataimport

15 stars 7.59 score 12 scripts 1 dependents

heike

x3ptools:Tools for Working with 3D Surface Measurements

The x3p file format is specified in ISO standard 5436:2000 to describe 3d surface measurements. 'x3ptools' allows reading, writing and basic modifications to the 3D surface measurements.

Maintained by Heike Hofmann. Last updated 6 months ago.

8 stars 7.48 score 281 scripts 2 dependents

momx

Momocs:Morphometrics using R

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

Maintained by Vincent Bonhomme. Last updated 1 years ago.

morphometrics

51 stars 7.42 score 346 scripts

thibautjombart

treespace:Statistical Exploration of Landscapes of Phylogenetic Trees

Tools for the exploration of distributions of phylogenetic trees. This package includes a 'shiny' interface which can be started from R using treespaceServer(). For further details see Jombart et al. (2017) <DOI:10.1111/1755-0998.12676>.

Maintained by Michelle Kendall. Last updated 2 years ago.

cpp

28 stars 7.39 score 63 scripts

jakobbossek

ecr:Evolutionary Computation in R

Framework for building evolutionary algorithms for both single- and multi-objective continuous or discrete optimization problems. A set of predefined evolutionary building blocks and operators is included. Moreover, the user can easily set up custom objective functions, operators, building blocks and representations sticking to few conventions. The package allows both a black-box approach for standard tasks (plug-and-play style) and a much more flexible white-box approach where the evolutionary cycle is written by hand.

Maintained by Jakob Bossek. Last updated 2 years ago.

combinatorial-optimization evolutionary-algorithm evolutionary-algorithms evolutionary-strategy genetic-algorithm-framework metaheuristics multi-objective-optimization optimization optimization-framework cpp

43 stars 7.36 score 89 scripts 2 dependents

sebastien-plutniak

archeoViz:Visualisation, Exploration, and Web Communication of Archaeological Spatial Data

An R 'Shiny' application for visual and statistical exploration and web communication of archaeological spatial data, either remains or sites. It offers interactive 3D and 2D visualisations (cross sections and maps of remains, timeline of the work made in a site) which can be exported in SVG and HTML formats. It performs simple spatial statistics (convex hull, regression surfaces, 2D kernel density estimation) and allows exporting data to other online applications for more complex methods. 'archeoViz' can be used offline locally or deployed on a server, either with interactive input of data or with a static data set. Example is provided at <https://analytics.huma-num.fr/archeoviz/en>.

Maintained by Sebastien Plutniak. Last updated 2 months ago.

archaeology archeology data-visualization

19 stars 7.23 score 6 scripts

strohne

volker:High-Level Functions for Tabulating, Charting and Reporting Survey Data

Craft polished tables and plots in Markdown reports. Simply choose whether to treat your data as counts or metrics, and the package will automatically generate well-designed default tables and plots for you. Boiled down to the basics, with labeling features and simple interactive reports. All functions are 'tidyverse' compatible.

Maintained by Jakob Jünger. Last updated 16 days ago.

5 stars 7.16 score 125 scripts

tomwenseleers

export:Streamlined Export of Graphs and Data Tables

Easily export 'R' graphs and statistical output to 'Microsoft Office' / 'LibreOffice', 'Latex' and 'HTML' Documents, using sensible defaults that result in publication-quality output with simple, straightforward commands. Output to 'Microsoft Office' is in editable 'DrawingML' vector format for graphs, and can use corporate template documents for styling. This enables the production of standardized reports and also allows for manual tidy-up of the layout of 'R' graphs in 'Powerpoint' before final publication. Export of graphs is flexible, and functions enable the currently showing R graph or the currently showing 'R' stats object to be exported, but also allow the graphical or tabular output to be passed as objects. The package relies on package 'officer' for export to 'Office' documents,and output files are also fully compatible with 'LibreOffice'. Base 'R', 'ggplot2' and 'lattice' plots are supported, as well as a wide variety of 'R' stats objects, via wrappers to xtable(), broom::tidy() and stargazer(), including aov(), lm(), glm(), lme(), glmnet() and coxph() as well as matrices and data frames and many more...

Maintained by Tom Wenseleers. Last updated 2 years ago.

195 stars 7.11 score 312 scripts

aidanmorales

rTwig:Realistic Quantitative Structure Models

Real Twig is a method to correct branch overestimation in quantitative structure models. Overestimated cylinders are correctly tapered using measured twig diameters of corresponding tree species. Supported quantitative structure modeling software includes 'TreeQSM', 'SimpleForest', 'Treegraph', and 'aRchi'. Also included is a novel database of twig diameters and tools for fractal analysis of point clouds.

Maintained by Aidan Morales. Last updated 27 days ago.

forestry lidar modeling qsm rcpp cpp

8 stars 7.10 score 13 scripts

chaisemartinpackages

DIDmultiplegtDYN:Estimation in Difference-in-Difference Designs with Multiple Groups and Periods

Estimation of heterogeneity-robust difference-in-differences estimators, with a binary, discrete, or continuous treatment, in designs where past treatments may affect the current outcome.

Maintained by Diego Ciccia. Last updated 4 days ago.

42 stars 7.10 score 19 scripts 1 dependents

ailich

MultiscaleDTM:Multi-Scale Geomorphometric Terrain Attributes

Calculates multi-scale geomorphometric terrain attributes from regularly gridded digital terrain models using a variable focal windows size (Ilich et al. (2023) <doi:10.1111/tgis.13067>).

Maintained by Alexander Ilich. Last updated 23 days ago.

openblas cpp

25 stars 7.05 score 30 scripts 2 dependents

vegandevs

vegan3d:Static and Dynamic 3D and Editable Interactive Plots for the 'vegan' Package

Static and dynamic 3D plots to be used with ordination results and in diversity analysis, especially with the vegan package.

Maintained by Jari Oksanen. Last updated 1 months ago.

19 stars 6.95 score 67 scripts 1 dependents

maxwell-geospatial

geodl:Geospatial Semantic Segmentation with Torch and Terra

Provides tools for semantic segmentation of geospatial data using convolutional neural network-based deep learning. Utility functions allow for creating masks, image chips, data frames listing image chips in a directory, and DataSets for use within DataLoaders. Additional functions are provided to serve as checks during the data preparation and training process. A UNet architecture can be defined with 4 blocks in the encoder, a bottleneck block, and 4 blocks in the decoder. The UNet can accept a variable number of input channels, and the user can define the number of feature maps produced in each encoder and decoder block and the bottleneck. Users can also choose to (1) replace all rectified linear unit (ReLU) activation functions with leaky ReLU or swish, (2) implement attention gates along the skip connections, (3) implement squeeze and excitation modules within the encoder blocks, (4) add residual connections within all blocks, (5) replace the bottleneck with a modified atrous spatial pyramid pooling (ASPP) module, and/or (6) implement deep supervision using predictions generated at each stage in the decoder. A unified focal loss framework is implemented after Yeung et al. (2022) <https://doi.org/10.1016/j.compmedimag.2021.102026>. We have also implemented assessment metrics using the 'luz' package including F1-score, recall, and precision. Trained models can be used to predict to spatial data without the need to generate chips from larger spatial extents. Functions are available for performing accuracy assessment. The package relies on 'torch' for implementing deep learning, which does not require the installation of a 'Python' environment. Raster geospatial data are handled with 'terra'. Models can be trained using a Compute Unified Device Architecture (CUDA)-enabled graphics processing unit (GPU); however, multi-GPU training is not supported by 'torch' in 'R'.

Maintained by Aaron Maxwell. Last updated 8 months ago.

12 stars 6.86 score 20 scripts

bryanhanson

HiveR:2D and 3D Hive Plots for R

Creates and plots 2D and 3D hive plots. Hive plots are a unique method of displaying networks of many types in which node properties are mapped to axes using meaningful properties rather than being arbitrarily positioned. The hive plot concept was invented by Martin Krzywinski at the Genome Science Center (www.hiveplot.net/). Keywords: networks, food webs, linnet, systems biology, bioinformatics.

Maintained by Bryan A. Hanson. Last updated 9 months ago.

72 stars 6.76 score 53 scripts 2 dependents

natverse

nat.nblast:NeuroAnatomy Toolbox ('nat') Extension for Assessing Neuron Similarity and Clustering

Extends package 'nat' (NeuroAnatomy Toolbox) by providing a collection of NBLAST-related functions for neuronal morphology comparison (Costa et al. (2016) <doi: 10.1016/j.neuron.2016.06.012>).

Maintained by Gregory Jefferis. Last updated 7 months ago.

morphological-analysis nblast neuroanatomy neuroanatomy-toolbox neurons

17 stars 6.69 score 96 scripts

bioc

MoonlightR:Identify oncogenes and tumor suppressor genes from omics data

Motivation: The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). Results: We present an R/bioconductor package called MoonlightR which returns a list of candidate driver genes for specific cancer types on the basis of TCGA expression data. The method first infers gene regulatory networks and then carries out a functional enrichment analysis (FEA) (implementing an upstream regulator analysis, URA) to score the importance of well-known biological processes with respect to the studied cancer type. Eventually, by means of random forests, MoonlightR predicts two specific roles for the candidate driver genes: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, MoonlightR can be used to discover OCGs and TSGs in the same cancer type. This may help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV) in breast cancer. In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments.

Maintained by Matteo Tiberti. Last updated 5 months ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network survival genesetenrichment networkenrichment

17 stars 6.57 score

dfsp-spirit

fsbrain:Managing and Visualizing Brain Surface Data

Provides high-level access to neuroimaging data from standard software packages like 'FreeSurfer' <http://freesurfer.net/> on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize data and statistical results directly in 'R'.

Maintained by Tim Schäfer. Last updated 4 months ago.

3d brain dti freesurfer mesh mri neuroimaging research surface visualization voxel

68 stars 6.49 score 15 scripts

molina-valero

FORTLS:Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes

Process automation of point cloud data derived from terrestrial-based technologies such as Terrestrial Laser Scanner (TLS) or Mobile Laser Scanner. 'FORTLS' enables (i) detection of trees and estimation of tree-level attributes (e.g. diameters and heights), (ii) estimation of stand-level variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories at stand-level, and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. (2022, <doi:10.1016/j.envsoft.2022.105337>).

Maintained by Juan Alberto Molina-Valero. Last updated 11 days ago.

forest-inventory forest-monitoring lidar-point-cloud cpp

23 stars 6.48 score 11 scripts

tidymodels

plsmod:Model Wrappers for Projection Methods

Bindings for additional regression models for use with the 'parsnip' package, including ordinary and spare partial least squares models for regression and classification (Rohart et al (2017) <doi:10.1371/journal.pcbi.1005752>).

Maintained by Max Kuhn. Last updated 6 months ago.

mixomics

14 stars 6.47 score 59 scripts 1 dependents

esteban-alfaro

adabag:Applies Multiclass AdaBoost.M1, SAMME and Bagging

It implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation estimation of the error can be done. Since version 2.0 the function margins() is available to calculate the margins for these classifiers. Also a higher flexibility is achieved giving access to the rpart.control() argument of 'rpart'. Four important new features were introduced on version 3.0, AdaBoost-SAMME (Zhu et al., 2009) is implemented and a new function errorevol() shows the error of the ensembles as a function of the number of iterations. In addition, the ensembles can be pruned using the option 'newmfinal' in the predict.bagging() and predict.boosting() functions and the posterior probability of each class for observations can be obtained. Version 3.1 modifies the relative importance measure to take into account the gain of the Gini index given by a variable in each tree and the weights of these trees. Version 4.0 includes the margin-based ordered aggregation for Bagging pruning (Guo and Boukir, 2013) and a function to auto prune the 'rpart' tree. Moreover, three new plots are also available importanceplot(), plot.errorevol() and plot.margins(). Version 4.1 allows to predict on unlabeled data. Version 4.2 includes the parallel computation option for some of the functions. Version 5.0 includes the Boosting and Bagging algorithms for label ranking (Albano, Sciandra and Plaia, 2023).

Maintained by Esteban Alfaro. Last updated 2 years ago.

5 stars 6.46 score 720 scripts 6 dependents

bioc

Moonlight2R:Identify oncogenes and tumor suppressor genes from omics data

The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). We present an updated version of the R/bioconductor package called MoonlightR, namely Moonlight2R, which returns a list of candidate driver genes for specific cancer types on the basis of omics data integration. The Moonlight framework contains a primary layer where gene expression data and information about biological processes are integrated to predict genes called oncogenic mediators, divided into putative tumor suppressors and putative oncogenes. This is done through functional enrichment analyses, gene regulatory networks and upstream regulator analyses to score the importance of well-known biological processes with respect to the studied cancer type. By evaluating the effect of the oncogenic mediators on biological processes or through random forests, the primary layer predicts two putative roles for the oncogenic mediators: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As gene expression data alone is not enough to explain the deregulation of the genes, a second layer of evidence is needed. We have automated the integration of a secondary mutational layer through new functionalities in Moonlight2R. These functionalities analyze mutations in the cancer cohort and classifies these into driver and passenger mutations using the driver mutation prediction tool, CScape-somatic. Those oncogenic mediators with at least one driver mutation are retained as the driver genes. As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, Moonlight2R can be used to discover OCGs and TSGs in the same cancer type. This may for instance help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV). In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments. An additional mechanistic layer evaluates if there are mutations affecting the protein stability of the transcription factors (TFs) of the TSGs and OCGs, as that may have an effect on the expression of the genes.

Maintained by Matteo Tiberti. Last updated 2 months ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network survival genesetenrichment networkenrichment

5 stars 6.41 score 43 scripts

atomashevic

transforEmotion:Sentiment Analysis for Text, Image and Video using Transformer Models

Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.

Maintained by Aleksandar Tomašević. Last updated 3 months ago.

26 stars 6.40 score 12 scripts

nspyrison

spinifex:Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data

Data visualization tours animates linear projection of multivariate data as its basis (ie. orientation) changes. The 'spinifex' packages generates paths for manual tours by manipulating the contribution of a single variable at a time Cook & Buja (1997) <doi:10.1080/10618600.1997.10474754>. Other types of tours, such as grand (random walk) and guided (optimizing some objective function) are available in the 'tourr' package Wickham et al. <doi:10.18637/jss.v040.i02>. 'spinifex' builds on 'tourr' and can render tours with 'gganimate' and 'plotly' graphics, and allows for exporting as an .html widget and as an .gif, respectively. This work is fully discussed in Spyrison & Cook (2020) <doi:10.32614/RJ-2020-027>.

Maintained by Nicholas Spyrison. Last updated 3 months ago.

dimension reduction tours visualization

3 stars 6.28 score 105 scripts 1 dependents

lem-usp

evolqg:Evolutionary Quantitative Genetics

Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.

Maintained by Diogo Melo. Last updated 11 months ago.

openblas cpp

10 stars 6.26 score 114 scripts

stla

uniformly:Uniform Sampling

Uniform sampling on various geometric shapes, such as spheres, ellipsoids, simplices.

Maintained by Stéphane Laurent. Last updated 2 years ago.

simulations

10 stars 6.21 score 109 scripts 1 dependents

ropensci

Rpolyhedra:Polyhedra Database

A polyhedra database scraped from various sources as R6 objects and 'rgl' visualizing capabilities.

Maintained by Alejandro Baranek. Last updated 5 months ago.

geometry polyhedra-database rgl

12 stars 6.21 score 30 scripts

spsanderson

RandomWalker:Generate Random Walks Compatible with the 'tidyverse'

Generates random walks of various types by providing a set of functions that are compatible with the 'tidyverse'. The functions provided in the package make it simple to create random walks with a variety of properties, such as how many simulations to run, how many steps to take, and the distribution of random walk itself.

Maintained by Steven Sanderson. Last updated 2 months ago.

random-walk random-walks rpackages

5 stars 6.05 score 5 scripts 1 dependents

bioc

timeOmics:Time-Course Multi-Omics data integration

timeOmics is a generic data-driven framework to integrate multi-Omics longitudinal data measured on the same biological samples and select key temporal features with strong associations within the same sample group. The main steps of timeOmics are: 1. Plaform and time-specific normalization and filtering steps; 2. Modelling each biological into one time expression profile; 3. Clustering features with the same expression profile over time; 4. Post-hoc validation step.

Maintained by Antoine Bodein. Last updated 5 months ago.

clustering featureextraction timecourse dimensionreduction software sequencing microarray metabolomics metagenomics proteomics classification regression immunooncology geneprediction multiplecomparison cluster integration multi-omics time-series

24 stars 5.98 score 10 scripts

mbinois

GPareto:Gaussian Processes for Pareto Front Estimation and Optimization

Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.

Maintained by Mickael Binois. Last updated 1 years ago.

cpp

16 stars 5.96 score 38 scripts 1 dependents

frankkramer-lab

mully:Create, Modify and Visualize Multi-Layered Networks

Allows the user to create graphs with multiple layers. The user can also modify the layers, the nodes, and the edges. The graph can also be visualized. Zaynab Hammoud and Frank Kramer (2018) <doi:10.3390/genes9110519>. More about multilayered graphs and their usage can be found in our review paper: Zaynab Hammoud and Frank Kramer (2020) <doi:10.1186/s41044-020-00046-0>.

Maintained by Zaynab Hammoud. Last updated 2 years ago.

big-networks data-visualization graph-theory graphs igraph multilayer-networks node-colored-graphs

45 stars 5.95 score 6 scripts

stla

cxhull:Convex Hull

Computes the convex hull in arbitrary dimension, based on the Qhull library (<http://www.qhull.org>). The package provides a complete description of the convex hull: edges, ridges, facets, adjacencies. Triangulation is optional.

Maintained by Stéphane Laurent. Last updated 1 years ago.

computational-geometry convex-hull

14 stars 5.93 score 81 scripts 5 dependents

italo-granato

snpReady:Preparing Genotypic Datasets in Order to Run Genomic Analysis

Three functions to clean, summarize and prepare genomic datasets to Genome Selection and Genome Association analysis and to estimate population genetic parameters.

Maintained by Italo Granato. Last updated 5 years ago.

4 stars 5.90 score 33 scripts

dewittpe

cpr:Control Polygon Reduction

Implementation of the Control Polygon Reduction and Control Net Reduction methods for finding parsimonious B-spline regression models.

Maintained by Peter DeWitt. Last updated 8 months ago.

openblas cpp

2 stars 5.87 score 62 scripts 1 dependents

cogbrainhealthlab

VertexWiseR:Simplified Vertex-Wise Analyses of Whole-Brain and Hippocampal Surface

Provides functions to run statistical analyses on surface-based neuroimaging data, computing measures including cortical thickness and surface area of the whole-brain and of the hippocampi. It can make use of 'FreeSurfer', 'fMRIprep', 'HCP' and 'CAT12' preprocessed datasets and 'HippUnfold' hippocampal segmentation outputs for a given sample by restructuring the data values into a single file. The single file can then be used by the package for analyses independently from its base dataset and without need for its access.

Maintained by Charly Billaud. Last updated 4 days ago.

1 stars 5.86 score 12 scripts

stla

RCDT:Fast 2D Constrained Delaunay Triangulation

Performs 2D Delaunay triangulation, constrained or unconstrained, with the help of the C++ library 'CDT'. A function to plot the triangulation is provided. The constrained Delaunay triangulation has applications in geographic information systems.

Maintained by Stéphane Laurent. Last updated 1 years ago.

constrained-delaunay-triangulation cpp delaunay-triangulation cpp

6 stars 5.85 score 39 scripts 2 dependents

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

elvanceyhan

pcds:Proximity Catch Digraphs and Their Applications

Contains the functions for construction and visualization of various families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2), for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) or uniformity in one, two and three dimensional cases. The package also has tools for generating points from these spatial patterns. The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi:10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs, and Central Similarity PCDs.

Maintained by Elvan Ceyhan. Last updated 2 years ago.

5.80 score 21 scripts 2 dependents

jcfaria

bpca:Biplot of Multivariate Data Based on Principal Components Analysis

Implements biplot (2d and 3d) of multivariate data based on principal components analysis and diagnostic tools of the quality of the reduction.

Maintained by José C. Faria. Last updated 1 years ago.

4 stars 5.79 score 34 scripts

luismurao

tenm:Temporal Ecological Niche Models

Implements methods and functions to calibrate time-specific niche models (multi-temporal calibration), letting users execute a strict calibration and selection process of niche models based on ellipsoids, as well as functions to project the potential distribution in the present and in global change scenarios.The 'tenm' package has functions to recover information that may be lost or overlooked while applying a data curation protocol. This curation involves preserving occurrences that may appear spatially redundant (occurring in the same pixel) but originate from different time periods. A novel aspect of this package is that it might reconstruct the fundamental niche more accurately than mono-calibrated approaches. The theoretical background of the package can be found in Peterson et al. (2011)<doi:10.5860/CHOICE.49-6266>.

Maintained by Luis Osorio-Olvera. Last updated 8 months ago.

6 stars 5.79 score 34 scripts

bioc

benchdamic:Benchmark of differential abundance methods on microbiome data

Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.

Maintained by Matteo Calgaro. Last updated 4 months ago.

metagenomics microbiome differentialexpression multiplecomparison normalization preprocessing software benchmark differential-abundance-methods

8 stars 5.78 score 8 scripts

mandymejia

BayesfMRI:Spatial Bayesian Methods for Task Functional MRI Studies

Performs a spatial Bayesian general linear model (GLM) for task functional magnetic resonance imaging (fMRI) data on the cortical surface. Additional models include group analysis and inference to detect thresholded areas of activation. Includes direct support for the 'CIFTI' neuroimaging file format. For more information see A. F. Mejia, Y. R. Yue, D. Bolin, F. Lindgren, M. A. Lindquist (2020) <doi:10.1080/01621459.2019.1611582> and D. Spencer, Y. R. Yue, D. Bolin, S. Ryan, A. F. Mejia (2022) <doi:10.1016/j.neuroimage.2022.118908>.

Maintained by Amanda Mejia. Last updated 22 days ago.

cpp

26 stars 5.77 score 19 scripts

pmontman

TSclust:Time Series Clustering Utilities

A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.

Maintained by Pablo Montero Manso. Last updated 5 years ago.

2 stars 5.76 score 170 scripts 8 dependents

trestletech

shinyRGL:Shiny Wrappers for RGL

Shiny wrappers for the RGL package. This package exposes RGL's ability to export WebGL visualization in a shiny-friendly format.

Maintained by Jeff Allen. Last updated 10 years ago.

52 stars 5.74 score 105 scripts

stla

gyro:Hyperbolic Geometry

Hyperbolic geometry in the Minkowski model and the Poincaré model. The methods are based on the gyrovector space theory developed by A. A. Ungar that can be found in the book 'Analytic Hyperbolic Geometry: Mathematical Foundations And Applications' <doi:10.1142/5914>. The package provides functions to plot three-dimensional hyperbolic polyhedra and to plot hyperbolic tilings of the Poincaré disk.

Maintained by Stéphane Laurent. Last updated 1 years ago.

geometry hyperbolic-geometry rgl cpp

4 stars 5.69 score 81 scripts 1 dependents

csafe-isu

cmcR:An Implementation of the 'Congruent Matching Cells' Method

An open-source implementation of the 'Congruent Matching Cells' method for cartridge case identification as proposed by Song (2013) <https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911193> as well as an extension of the method proposed by Tong et al. (2015) <doi:10.6028/jres.120.008>. Provides a wide range of pre, inter, and post-processing options when working with cartridge case scan data and their associated comparisons. See the cmcR package website for more details and examples.

Maintained by Joe Zemmels. Last updated 2 years ago.

4 stars 5.68 score 60 scripts

ropensci

fireexposuR:Compute and Visualize Wildfire Exposure

This package computes and visualizes wildfire exposure using the methods documented in a series of scientific publications.

Maintained by Air Forbes. Last updated 5 days ago.

5 stars 5.56 score 4 scripts

kisungyou

maotai:Tools for Matrix Algebra, Optimization and Inference

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

Maintained by Kisung You. Last updated 14 days ago.

openblas cpp openmp

8 stars 5.51 score 15 scripts 9 dependents

molinlab

Holomics:An User-Friendly R 'shiny' Application for Multi-Omics Data Integration and Analysis

A 'shiny' application, which allows you to perform single- and multi-omics analyses using your own omics datasets. After the upload of the omics datasets and a metadata file, single-omics is performed for feature selection and dataset reduction. These datasets are used for pairwise- and multi-omics analyses, where automatic tuning is done to identify correlations between the datasets - the end goal of the recommended 'Holomics' workflow. Methods used in the package were implemented in the package 'mixomics' by Florian Rohart,Benoît Gautier,Amrit Singh,Kim-Anh Lê Cao (2017) <doi:10.1371/journal.pcbi.1005752> and are described there in further detail.

Maintained by Katharina Munk. Last updated 10 months ago.

7 stars 5.45 score 7 scripts

bioc

PLSDAbatch:PLSDA-batch

A novel framework to correct for batch effects prior to any downstream analysis in microbiome data based on Projection to Latent Structures Discriminant Analysis. The main method is named “PLSDA-batch”. It first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data whilst preserving biological variation of interest. PLSDA-batch is highly suitable for microbiome data as it is non-parametric, multivariate and allows for ordination and data visualisation. Combined with centered log-ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far. Two other variants are proposed for 1/ unbalanced batch x treatment designs that are commonly encountered in studies with small sample sizes, and for 2/ selection of discriminative variables amongst treatment groups to avoid overfitting in classification problems. These two variants have widened the scope of applicability of PLSDA-batch to different data settings.

Maintained by Yiwen (Eva) Wang. Last updated 5 months ago.

statisticalmethod dimensionreduction principalcomponent classification microbiome batcheffect normalization visualization

13 stars 5.37 score 18 scripts

teazrq

RLT:Reinforcement Learning Trees

Random forest with a variety of additional features for regression, classification, survival analysis and graphical model. New features include parallel computing with OpenMP, reproduciblity with random seeds, variance and confidence band estimations, embedded model for selecting splitting varibles and constructing linear combination splits, observaton and variable weights, setting and tracking subjects used in each tree, etc.

Maintained by Ruoqing Zhu. Last updated 5 months ago.

openblas cpp openmp

11 stars 5.36 score 21 scripts

beatrizpateiro

alphashape3d:Implementation of the 3D Alpha-Shape for the Reconstruction of 3D Sets from a Point Cloud

Implementation in R of the alpha-shape of a finite set of points in the three-dimensional space. The alpha-shape generalizes the convex hull and allows to recover the shape of non-convex and even non-connected sets in 3D, given a random sample of points taken into it. Besides the computation of the alpha-shape, this package provides users with functions to compute the volume of the alpha-shape, identify the connected components and facilitate the three-dimensional graphical visualization of the estimated set.

Maintained by Beatriz Pateiro-Lopez. Last updated 2 years ago.

2 stars 5.34 score 82 scripts 5 dependents

biostatomics

Coxmos:Cox MultiBlock Survival

This software package provides Cox survival analysis for high-dimensional and multiblock datasets. It encompasses a suite of functions dedicated from the classical Cox regression to newest analysis, including Cox proportional hazards model, Stepwise Cox regression, and Elastic-Net Cox regression, Sparse Partial Least Squares Cox regression (sPLS-COX) incorporating three distinct strategies, and two Multiblock-PLS Cox regression (MB-sPLS-COX) methods. This tool is designed to adeptly handle high-dimensional data, and provides tools for cross-validation, plot generation, and additional resources for interpreting results. While references are available within the corresponding functions, key literature is mentioned below. Terry M Therneau (2024) <https://CRAN.R-project.org/package=survival>, Noah Simon et al. (2011) <doi:10.18637/jss.v039.i05>, Philippe Bastien et al. (2005) <doi:10.1016/j.csda.2004.02.005>, Philippe Bastien (2008) <doi:10.1016/j.chemolab.2007.09.009>, Philippe Bastien et al. (2014) <doi:10.1093/bioinformatics/btu660>, Kassu Mehari Beyene and Anouar El Ghouch (2020) <doi:10.1002/sim.8671>, Florian Rohart et al. (2017) <doi:10.1371/journal.pcbi.1005752>.

Maintained by Pedro Salguero García. Last updated 25 days ago.

1 stars 5.30 score 5 scripts

christiangoueguel

HotellingEllipse:Hotelling’s T-Squared Statistic and Ellipse

Functions to calculate the Hotelling’s T-squared statistic and corresponding confidence ellipses. Provides the semi-axes of the Hotelling’s T-squared ellipses at 95% and 99% confidence levels. Enables users to obtain the coordinates in two or three dimensions at user-defined confidence levels, allowing for the construction of 2D or 3D ellipses with customized confidence levels. Bro and Smilde (2014) <DOI:10.1039/c3ay41907j>. Brereton (2016) <DOI:10.1002/cem.2763>.

Maintained by Christian L. Goueguel. Last updated 3 months ago.

confidence-ellipse hotelling-ellipse hotelling-s-t-square hotelling-t2 hotellings-t2-distribution multivariate-distribution outliers partial-least-squares-regression pca pls principal-component-analysis

7 stars 5.29 score 14 scripts

bioc

MultiRNAflow:An R package for integrated analysis of temporal RNA-seq data with multiple biological conditions

Our R package MultiRNAflow provides an easy to use unified framework allowing to automatically make both unsupervised and supervised (DE) analysis for datasets with an arbitrary number of biological conditions and time points. In particular, our code makes a deep downstream analysis of DE information, e.g. identifying temporal patterns across biological conditions and DE genes which are specific to a biological condition for each time.

Maintained by Rodolphe Loubaton. Last updated 5 months ago.

sequencing rnaseq geneexpression transcription timecourse preprocessing visualization normalization principalcomponent clustering differentialexpression genesetenrichment pathways

6 stars 5.26 score 4 scripts

stla

tessellation:Delaunay and Voronoï Tessellations

Delaunay and Voronoï tessellations, with emphasis on the two-dimensional and the three-dimensional cases (the package provides functions to plot the tessellations for these cases). Delaunay tessellations are computed in C with the help of the 'Qhull' library <http://www.qhull.org/>.

Maintained by Stéphane Laurent. Last updated 1 years ago.

c delaunay-triangulation voronoi-tessellation

17 stars 5.23 score 67 scripts 1 dependents

fbertran

plsRcox:Partial Least Squares Regression for Cox Models and Related Techniques

Provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models in high dimensional settings <doi:10.1093/bioinformatics/btu660>, Bastien, P., Bertrand, F., Meyer N., Maumy-Bertrand, M. (2015), Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data, Bioinformatics, 31(3):397-404. Cross validation criteria were studied in <arXiv:1810.02962>, Bertrand, F., Bastien, Ph. and Maumy-Bertrand, M. (2018), Cross validating extensions of kernel, sparse or regular partial least squares regression models to censored data.

Maintained by Frederic Bertrand. Last updated 2 years ago.

4 stars 5.13 score 56 scripts 2 dependents

spsanderson

healthyverse:Easily Install and Load the 'healthyverse'

The 'healthyverse' is a set of packages that work in harmony because they share common data representations and 'API' design. This package is designed to make it easy to install and load multiple 'healthyverse' packages in a single step.

Maintained by Steven Sanderson. Last updated 6 months ago.

analytics healthcare healthcare-application installation installer meta packages

11 stars 5.12 score 24 scripts

annajenul

UBayFS:A User-Guided Bayesian Framework for Ensemble Feature Selection (UBayFS)

Implements the user-guided Bayesian framework for ensemble feature selection (UBayFS) : Jenul et al., (2022) <doi:10.1007/s10994-022-06221-9>.

Maintained by Anna Jenul. Last updated 2 years ago.

bayesian-statistics ensemble-models feature-selection user-knowledge

5 stars 5.11 score 13 scripts

vbaliga

gaussplotR:Fit, Predict and Plot 2D Gaussians

Functions to fit two-dimensional Gaussian functions, predict values from fits, and produce plots of predicted data via either 'ggplot2' or base R plotting.

Maintained by Vikram B. Baliga. Last updated 4 years ago.

2d-gaussian gaussian gaussian-fit gaussian-interpolation gaussian-plot gaussian-volume plotting

4 stars 5.10 score 21 scripts

bioc

geomeTriD:A R/Bioconductor package for interactive 3D plot of epigenetic data or single cell data

geomeTriD (Three Dimensional Geometry Package) create interactive 3D plots using the GL library with the 'three.js' visualization library (https://threejs.org) or the rgl library. In addition to creating interactive 3D plots, the application also generates simplified models in 2D. These 2D models provide a more straightforward visual representation, making it easier to analyze and interpret the data quickly. This functionality ensures that users have access to both detailed three-dimensional visualizations and more accessible two-dimensional views, catering to various analytical needs.

Maintained by Jianhong Ou. Last updated 2 months ago.

visualization

1 stars 5.10 score 7 scripts

hypertidy

anglr:Mesh Topology and Visualization for Spatial Data

Gives direct access to generic 3D tools and provides a full suite of mesh-creation and 3D plotting functions. By extending the 'rgl' package conversion and visualization functions for the 'mesh3d' class a wide variety of complex spatial data can be brought into 3D scenes. These tools allow for spatial raster, polygons, and lines that are common in 'GIS' contexts to be converted into mesh forms with high flexibility and the ability to integrate disparate data types. Vector and raster data can be seamlessly combined as meshes, and surfaces can be set to have material properties based on data values or with image textures. Textures and other data combinations use projection transformations to map between coordinate systems, and objects can be easily visualized in an interactive scene at any stage. This package relies on the 'RTriangle' package for high-quality triangular meshing which is licensed restrictively under 'CC BY-NC-SA 4.0'.

Maintained by Michael D. Sumner. Last updated 2 years ago.

82 stars 5.09 score 99 scripts

bioc

DepecheR:Determination of essential phenotypic elements of clusters in high-dimensional entities

The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.

Maintained by Jakob Theorell. Last updated 5 months ago.

software cellbasedassays transcription differentialexpression datarepresentation immunooncology transcriptomics classification clustering dimensionreduction featureextraction flowcytometry rnaseq singlecell visualization cpp

5.08 score 15 scripts

dmurdoch

rgl2gltf:Read and Write '.gltf' and '.glb' Files

The 'glTF' file format is used to describe 3D models. This package provides read and write functions to work with it.

Maintained by Duncan Murdoch. Last updated 4 months ago.

gltf2 graphics rgl cpp

8 stars 5.05 score 14 scripts

marekslenker

MorphoTools2:Multivariate Morphometric Analysis

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

Maintained by Marek Šlenker. Last updated 6 months ago.

7 stars 5.02 score 9 scripts

r-forge

plasma:Partial LeAst Squares for Multiomic Analysis

Contains tools for supervised analyses of incomplete, overlapping multiomics datasets. Applies partial least squares in multiple steps to find models that predict survival outcomes. See Yamaguchi et al. (2023) <doi:10.1101/2023.03.10.532096>.

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

4.97 score 13 scripts

stevenvb12

patternize:Quantification of Color Pattern Variation

Quantification of variation in organismal color patterns as obtained from image data. Patternize defines homology between pattern positions across images either through fixed landmarks or image registration. Pattern identification is performed by categorizing the distribution of colors using RGB thresholds or image segmentation.

Maintained by Steven Van Belleghem. Last updated 9 months ago.

31 stars 4.97 score 30 scripts

rikenbit

iTensor:ICA-Based Matrix/Tensor Decomposition

Some functions for performing ICA, MICA, Group ICA, and Multilinear ICA are implemented. ICA, MICA/Group ICA, and Multilinear ICA extract statistically independent components from single matrix, multiple matrices, and single tensor, respectively. For the details of these methods, see the reference section of GitHub README.md <https://github.com/rikenbit/iTensor>.

Maintained by Koki Tsuyuzaki. Last updated 2 years ago.

1 stars 4.95 score 2 scripts 1 dependents

bioc

RDRToolbox:A package for nonlinear dimension reduction with Isomap and LLE.

A package for nonlinear dimension reduction using the Isomap and LLE algorithm. It also includes a routine for computing the Davis-Bouldin-Index for cluster validation, a plotting tool and a data generator for microarray gene expression data and for the Swiss Roll dataset.

Maintained by Christoph Bartenhagen. Last updated 5 months ago.

dimensionreduction featureextraction visualization clustering microarray

4.88 score 54 scripts

friendly

genridge:Generalized Ridge Trace Plots for Ridge Regression

The genridge package introduces generalizations of the standard univariate ridge trace plot used in ridge regression and related methods. These graphical methods show both bias (actually, shrinkage) and precision, by plotting the covariance ellipsoids of the estimated coefficients, rather than just the estimates themselves. 2D and 3D plotting methods are provided, both in the space of the predictor variables and in the transformed space of the PCA/SVD of the predictors.

Maintained by Michael Friendly. Last updated 4 months ago.

bias-variance graphics principal-component-analysis regression-models ridge-regression singular-value-decomposition

4 stars 4.84 score 69 scripts

r-lidar

lidRviewer:3D point cloud viewer

An advanced point cloud viewer designed to fluidly display hundreds of millions of points while using minimal memory. This package is intended as a replacement for rgl in lidR when the point cloud size exceeds what rgl can handle.

Maintained by Jean-Romain Roussel. Last updated 3 months ago.

libsdl2 libglu libglvnd cpp

84 stars 4.83 score 7 scripts

cardiomoon

predict3d:Draw Three Dimensional Predict Plot Using Package 'rgl'

Draw 2 dimensional and three dimensional plot for multiple regression models using package 'ggplot2' and 'rgl'. Supports linear models (lm), generalized linear models (glm) and local polynomial regression fittings (loess).

Maintained by Keon-Woong Moon. Last updated 12 months ago.

7 stars 4.82 score 19 scripts

cubiczebra

TPMplt:Tool-Kit for Dynamic Materials Model and Thermal Processing Maps

Provides a simple approach for constructing dynamic materials modeling suggested by Prasad and Gegel (1984) <doi:10.1007/BF02664902>. It can easily generate various processing-maps based on this model as well. The calculation result in this package contains full materials constants, information about power dissipation efficiency factor, and rheological properties, can be exported completely also, through which further analysis and customized plots will be applicable as well.

Maintained by Chen Zhang. Last updated 6 months ago.

2 stars 4.76 score 29 scripts

davidcsterratt

retistruct:Retinal Reconstruction Program

Reconstructs retinae by morphing a flat surface with cuts (a dissected flat-mount retina) onto a curvilinear surface (the standard retinal shape). It can estimate the position of a point on the intact adult retina to within 8 degrees of arc (3.6% of nasotemporal axis). The coordinates in reconstructed retinae can be transformed to visuotopic coordinates. For more details see Sterratt, D. C., Lyngholm, D., Willshaw, D. J. and Thompson, I. D. (2013) <doi:10.1371/journal.pcbi.1002921>.

Maintained by David C. Sterratt. Last updated 2 days ago.

8 stars 4.75 score

jakobbossek

mcMST:A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem

Algorithms to approximate the Pareto-front of multi-criteria minimum spanning tree problems.

Maintained by Jakob Bossek. Last updated 2 years ago.

evolutionary-algorithms mcmst minimum-spanning-trees multi-objective-optimization spanningtrees

4 stars 4.73 score 27 scripts

nspyrison

cheem:Interactively Explore Local Explanations with the Radial Tour

Given a non-linear model, calculate the local explanation. We purpose view the data space, explanation space, and model residuals as ensemble graphic interactive on a shiny application. After an observation of interest is identified, the normalized variable importance of the local explanation is used as a 1D projection basis. The support of the local explanation is then explored by changing the basis with the use of the radial tour <doi:10.32614/RJ-2020-027>; <doi:10.1080/10618600.1997.10474754>.

Maintained by Nicholas Spyrison. Last updated 1 years ago.

2 stars 4.73 score 54 scripts

p-rocha

SoundShape:Sound Waves Onto Morphometric Data

Implement a promising, and yet little explored protocol for bioacoustical analysis, the eigensound method by MacLeod, Krieger and Jones (2013) <doi:10.4404/hystrix-24.1-6299>. Eigensound is a multidisciplinary method focused on the direct comparison between stereotyped sounds from different species. 'SoundShape', in turn, provide the tools required for anyone to go from sound waves to Principal Components Analysis, using tools extracted from traditional bioacoustics (i.e. 'tuneR' and 'seewave' packages), geometric morphometrics (i.e. 'geomorph' package) and multivariate analysis (e.g. 'stats' package). For more information, please see Rocha and Romano (2021) and check 'SoundShape' repository on GitHub for news and updates <https://github.com/p-rocha/SoundShape>.

Maintained by Pedro Rocha. Last updated 6 months ago.

9 stars 4.73 score 12 scripts

bioc

NormqPCR:Functions for normalisation of RT-qPCR data

Functions for the selection of optimal reference genes and the normalisation of real-time quantitative PCR data.

Maintained by James Perkins. Last updated 5 months ago.

microtitreplateassay geneexpression qpcr

4.72 score 26 scripts

christiangoueguel

ConfidenceEllipse:Computation of 2D and 3D Elliptical Joint Confidence Regions

Computing elliptical joint confidence regions at a specified confidence level. It provides the flexibility to estimate either classical or robust confidence regions, which can be visualized in 2D or 3D plots. The classical approach assumes normality and uses the mean and covariance matrix to define the confidence regions. Alternatively, the robustified version employs estimators like minimum covariance determinant (MCD) and M-estimator, making them less sensitive to outliers and departures from normality. Furthermore, the functions allow users to group the dataset based on categorical variables and estimate separate confidence regions for each group. This capability is particularly useful for exploring potential differences or similarities across subgroups within a dataset. Varmuza and Filzmoser (2009, ISBN:978-1-4200-5947-2). Johnson and Wichern (2007, ISBN:0-13-187715-1). Raymaekers and Rousseeuw (2019) <DOI:10.1080/00401706.2019.1677270>.

Maintained by Christian L. Goueguel. Last updated 11 months ago.

confidence-ellipse confidence-ellipsoid confidence-region multivariate-distribution outliers-detection robust-statistics

1 stars 4.70 score

forsbergpyschometrics

D3mirt:Descriptive 3D Multidimensional Item Response Theory Modelling

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

Maintained by Erik Forsberg. Last updated 1 months ago.

4.70 score 4 scripts

cygei

mixtree:A Statistical Framework for Comparing Sets of Trees

Apply hypothesis testing methods to assess differences between sets of trees.

Maintained by Cyril Geismar. Last updated 1 months ago.

4.70 score

tguillerme

treats:Trees and Traits Simulations

A modular package for simulating phylogenetic trees and species traits jointly. Trees can be simulated using modular birth-death parameters (e.g. changing starting parameters or algorithm rules). Traits can be simulated in any way designed by the user. The growth of the tree and the traits can influence each other through modifiers objects providing rules for affecting each other. Finally, events can be created to modify both the tree and the traits under specific conditions ( Guillerme, 2024 <DOI:10.1111/2041-210X.14306>).

Maintained by Thomas Guillerme. Last updated 2 days ago.

3 stars 4.69 score 19 scripts

mlampros

fitbitViz:'Fitbit' Visualizations

Connection to the 'Fitbit' Web API <https://dev.fitbit.com/build/reference/web-api/> by including 'ggplot2' Visualizations, 'Leaflet' and 3-dimensional 'Rayshader' Maps. The 3-dimensional 'Rayshader' Map requires the installation of the 'CopernicusDEM' R package which includes the 30- and 90-meter elevation data.

Maintained by Lampros Mouselimis. Last updated 1 years ago.

blogdown fitbit fitbit-api github-actions visualization

9 stars 4.65 score 1 scripts

telfer

pressuRe:Imports, Processes, and Visualizes Biomechanical Pressure Data

Allows biomechanical pressure data from a range of systems to be imported and processed in a reproducible manner. Automatic and manual tools are included to let the user define regions (masks) to be analyzed. Also includes functions for visualizing and animating pressure data. Example methods are described in Shi et al., (2022) <doi:10.1038/s41598-022-19814-0>, Lee et al., (2014) <doi:10.1186/1757-1146-7-18>, van der Zward et al., (2014) <doi:10.1186/1757-1146-7-20>, Najafi et al., (2010) <doi:10.1016/j.gaitpost.2009.09.003>, Cavanagh and Rodgers (1987) <doi:10.1016/0021-9290(87)90255-7>.

Maintained by Scott Telfer. Last updated 6 days ago.

2 stars 4.62 score

ggseg

ggsegExtra:Extra Utilities for the 'ggseg' and 'ggseg3d' Plotting Tools

Contains functions to create new data sets compatible with the 'ggseg' and 'ggseg3d' packages for plotting brain segmentations through R. Requires several external software to be installed on the system for atlas creations to work, and most of these are not available for windows. But atlas creation tools exist for 2d simple features data, and also 3d tri-surface mesh plots. Also has a list of compatible data sets and functions for easy installation of these.

Maintained by Athanasia Mo Mowinckel. Last updated 3 years ago.

55 stars 4.59 score 70 scripts

kisungyou

CovTools:Statistical Tools for Covariance Analysis

Covariance is of universal prevalence across various disciplines within statistics. We provide a rich collection of geometric and inferential tools for convenient analysis of covariance structures, topics including distance measures, mean covariance estimator, covariance hypothesis test for one-sample and two-sample cases, and covariance estimation. For an introduction to covariance in multivariate statistical analysis, see Schervish (1987) <doi:10.1214/ss/1177013111>.

Maintained by Kisung You. Last updated 2 years ago.

covariance covariance-estimation openblas cpp

13 stars 4.55 score 55 scripts

discoleo

Rpdb:Read, Write, Visualize and Manipulate PDB Files

Provides tools to read, write, visualize Protein Data Bank (PDB) files and perform some structural manipulations.

Maintained by Leonard Mada. Last updated 9 days ago.

4.53 score 68 scripts

teazrq

orthoDr:Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization

Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2019) <arXiv:1704.05046> and Zhou, Zhu & Zeng (2021) <arXiv:1802.06156>. It also serves as a general purpose optimization solver for problems with orthogonality constraints. Parallel computing for approximating the gradient is enabled through 'OpenMP'.

Maintained by Ruoqing Zhu. Last updated 3 years ago.

openblas cpp openmp

8 stars 4.53 score 14 scripts 2 dependents

paulocortez4

rminer:Data Mining Classification and Regression Methods

Facilitates the use of data mining algorithms in classification and regression (including time series forecasting) tasks by presenting a short and coherent set of functions. Versions: 1.4.8 improved help, several warning and error code fixes (more stable version, all examples run correctly); 1.4.7 improved Importance function and examples, minor error fixes; 1.4.6 / 1.4.5 / 1.4.4 new automated machine learning (AutoML) and ensembles, via improved fit(), mining() and mparheuristic() functions, and new categorical preprocessing, via improved delevels() function; 1.4.3 new metrics (e.g., macro precision, explained variance), new "lssvm" model and improved mparheuristic() function; 1.4.2 new "NMAE" metric, "xgboost" and "cv.glmnet" models (16 classification and 18 regression models); 1.4.1 new tutorial and more robust version; 1.4 - new classification and regression models, with a total of 14 classification and 15 regression methods, including: Decision Trees, Neural Networks, Support Vector Machines, Random Forests, Bagging and Boosting; 1.3 and 1.3.1 - new classification and regression metrics; 1.2 - new input importance methods via improved Importance() function; 1.0 - first version.

Maintained by Paulo Cortez. Last updated 5 months ago.

3 stars 4.52 score 536 scripts

bioc

TrajectoryGeometry:This Package Discovers Directionality in Time and Pseudo-times Series of Gene Expression Patterns

Given a time series or pseudo-times series of gene expression data, we might wish to know: Do the changes in gene expression in these data exhibit directionality? Are there turning points in this directionality. Do different subsets of the data move in different directions? This package uses spherical geometry to probe these sorts of questions. In particular, if we are looking at (say) the first n dimensions of the PCA of gene expression, directionality can be detected as the clustering of points on the (n-1)-dimensional sphere.

Maintained by Michael Shapiro. Last updated 5 months ago.

biologicalquestion statisticalmethod geneexpression singlecell

4.48 score 7 scripts

muschellij2

brainR:Helper Functions to 'misc3d' and 'rgl' Packages for Brain Imaging

This includes functions for creating 3D and 4D images using 'WebGL', 'rgl', and 'JavaScript' commands. This package relies on the X toolkit ('XTK', <https://github.com/xtk/X#readme>).

Maintained by John Muschelli. Last updated 2 days ago.

11 stars 4.45 score 17 scripts 1 dependents

friendly

mvinfluence:Influence Measures and Diagnostic Plots for Multivariate Linear Models

Computes regression deletion diagnostics for multivariate linear models and provides some associated diagnostic plots. The diagnostic measures include hat-values (leverages), generalized Cook's distance, and generalized squared 'studentized' residuals. Several types of plots to detect influential observations are provided.

Maintained by Michael Friendly. Last updated 3 years ago.

multivariate-analysis multivariate-linear-regression statistics visualization

2 stars 4.41 score 26 scripts

bioc

PRONE:The PROteomics Normalization Evaluator

High-throughput omics data are often affected by systematic biases introduced throughout all the steps of a clinical study, from sample collection to quantification. Normalization methods aim to adjust for these biases to make the actual biological signal more prominent. However, selecting an appropriate normalization method is challenging due to the wide range of available approaches. Therefore, a comparative evaluation of unnormalized and normalized data is essential in identifying an appropriate normalization strategy for a specific data set. This R package provides different functions for preprocessing, normalizing, and evaluating different normalization approaches. Furthermore, normalization methods can be evaluated on downstream steps, such as differential expression analysis and statistical enrichment analysis. Spike-in data sets with known ground truth and real-world data sets of biological experiments acquired by either tandem mass tag (TMT) or label-free quantification (LFQ) can be analyzed.

Maintained by Lis Arend. Last updated 9 days ago.

proteomics preprocessing normalization differentialexpression visualization data-analysis evaluation

2 stars 4.41 score 9 scripts

saitoutoshihide

rgl.cry:'cry' and 'rgl' — Applications in Crystallography

Visualizing crystal structures and selected area electron diffraction (SAED) patterns. It provides functions cry_demo() and dp_demo() to load a file in 'CIF' (Crystallographic Information Framework) formats and display crystal structures and electron diffraction patterns. The function dp_demo() also performs simple simulation of powder X-ray diffraction (PXRD) patterns, and the results can be saved to a file in the working directory. The package has been tested on several platforms, including Linux on 'Crostini' with a Core™ m3-8100Y Chromebook, I found that even on this low-powered platform, the performance was acceptable. T. Hanashima (2001) <https://www2.kek.jp/imss/pf/tools/sasaki/sinram/sinram.html> Todd Helmenstine (2019) <https://sciencenotes.org/molecule-atom-colors-cpk-colors/> Wikipedia contributors (2023) <https://en.wikipedia.org/w/index.php?title=Atomic_radius&oldid=1179864711>.

Maintained by Toshihide Saitou. Last updated 5 months ago.

4.40 score 3 scripts

bioc

m6Aboost:m6Aboost

This package can help user to run the m6Aboost model on their own miCLIP2 data. The package includes functions to assign the read counts and get the features to run the m6Aboost model. The miCLIP2 data should be stored in a GRanges object. More details can be found in the vignette.

Maintained by You Zhou. Last updated 5 months ago.

sequencing epigenetics genetics experimenthubsoftware

2 stars 4.30 score 5 scripts

matildabrown

hyperoverlap:Overlap Detection in n-Dimensional Space

Uses support vector machines to identify a perfectly separating hyperplane (linear or curvilinear) between two entities in high-dimensional space. If this plane exists, the entities do not overlap. Applications include overlap detection in morphological, resource or environmental dimensions. More details can be found in: Brown et al. (2020) <doi:10.1111/2041-210X.13363> .

Maintained by Matilda Brown. Last updated 4 years ago.

4 stars 4.30 score 7 scripts

emallickhossain

ivdoctr:Ensures Mutually Consistent Beliefs When Using IVs

Uses data and researcher's beliefs on measurement error and instrumental variable (IV) endogeneity to generate the space of consistent beliefs across measurement error, instrument endogeneity, and instrumental relevance for IV regressions. Package based on DiTraglia and Garcia-Jimeno (2020) <doi:10.1080/07350015.2020.1753528>.

Maintained by Mallick Hossain. Last updated 3 years ago.

openblas cpp

4.29 score 13 scripts

kleebaum

geoelectrics:3D-Visualization of Geoelectric Resistivity Measurement Profiles

Visualizes two-dimensional geoelectric resistivity measurement profiles in three dimensions.

Maintained by Anja Kleebaum. Last updated 2 years ago.

13 stars 4.28 score 29 scripts

kisungyou

T4cluster:Tools for Cluster Analysis

Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.

Maintained by Kisung You. Last updated 4 years ago.

openblas cpp openmp

6 stars 4.26 score 9 scripts 2 dependents

pierreroudier

hillshader:Create Hillshade Relief Maps Using Ray-Tracing

A set of tools to create georeferenced hillshade relief raster maps using ray-tracing and other advanced hill-shading techniques. It includes a wrapper function to create a georeferenced, ray-traced hillshade map from a digital elevation model, and other functions that can be used in a rayshader pipeline.

Maintained by Pierre Roudier. Last updated 1 years ago.

34 stars 4.23 score 3 scripts

blecigne

VoxR:Trees Geometry and Morphology from Unstructured TLS Data

Tools for 3D point cloud voxelisation, projection, geometrical and morphological description of trees (DBH, height, volume, crown diameter), analyses of temporal changes between different measurement times, distance based clustering and visualisation of 3D voxel clouds and 2D projection. Most analyses and algorithms provided in the package are based on the concept of space exploration and are described in Lecigne et al. (2018, https://doi.org/10.1093/aob/mcx095).

Maintained by Bastien Lecigne. Last updated 4 years ago.

6 stars 4.21 score 18 scripts 1 dependents

mandymejia

hrf:Hemodynamic Response Function

Computes the hemodynamic response function (HRF) for task functional magnetic resonance imaging (fMRI) data. Also includes functions for constructing a design matrix from task fMRI event timings, and for comparing multiple design matrices in a general linear model (GLM). A wrapper function is provided for GLM analysis of CIFTI-format data. Lastly, there are supporting functions which provide visual summaries of the HRFs and design matrices.

Maintained by Amanda Mejia. Last updated 2 months ago.

1 stars 4.18 score

karlines

OceanView:Visualisation of Oceanographic Data and Model Output

Functions for transforming and viewing 2-D and 3-D (oceanographic) data and model output.

Maintained by Karline Soetaert. Last updated 1 years ago.

fortran

4.08 score 60 scripts

cran

Directional:A Collection of Functions for Directional Data Analysis

A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include: a) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. <doi:10.1007/s11222-019-09872-2>. d) Tsagris M. and Alenazi A. (2024). "An investigation of hypothesis testing procedures for circular and spherical mean vectors". Communications in Statistics-Simulation and Computation, 53(3): 1387--1408. <doi:10.1080/03610918.2022.2045499>. e) Yu Z. and Huang X. (2024). A new parameterization for elliptically symmetric angular Gaussian distributions of arbitrary dimension. Electronic Journal of Statistics, 18(1): 301--334. <doi:10.1214/23-EJS2210>. f) Tsagris M. and Alzeley O. (2024). "Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling". Australian & New Zealand Journal of Statistics (Accepted for publication). <doi:10.1111/anzs.12434>. g) Tsagris M., Papastamoulis P. and Kato S. (2024). "Directional data analysis: spherical Cauchy or Poisson kernel-based distribution". Statistics and Computing (Accepted for publication). <doi:10.48550/arXiv.2409.03292>.

Maintained by Michail Tsagris. Last updated 2 months ago.

3 stars 4.06 score 3 dependents

natverse

nat.templatebrains:NeuroAnatomy Toolbox ('nat') Extension for Handling Template Brains

Extends package 'nat' (NeuroAnatomy Toolbox) by providing objects and functions for handling template brains.

Maintained by Gregory Jefferis. Last updated 2 years ago.

bridging-registrations image-registration natverse neuroanatomy neuroanatomy-toolbox

3 stars 4.05 score 37 scripts

psychbruce

PsychWordVec:Word Embedding Research Framework for Psychological Science

An integrative toolbox of word embedding research that provides: (1) a collection of 'pre-trained' static word vectors in the '.RData' compressed format <https://psychbruce.github.io/WordVector_RData.pdf>; (2) a series of functions to process, analyze, and visualize word vectors; (3) a range of tests to examine conceptual associations, including the Word Embedding Association Test <doi:10.1126/science.aal4230> and the Relative Norm Distance <doi:10.1073/pnas.1720347115>, with permutation test of significance; (4) a set of training methods to locally train (static) word vectors from text corpora, including 'Word2Vec' <arXiv:1301.3781>, 'GloVe' <doi:10.3115/v1/D14-1162>, and 'FastText' <arXiv:1607.04606>; (5) a group of functions to download 'pre-trained' language models (e.g., 'GPT', 'BERT') and extract contextualized (dynamic) word vectors (based on the R package 'text').

Maintained by Han-Wu-Shuang Bao. Last updated 1 years ago.

22 stars 4.04 score 10 scripts

pbourkey

polymapR:Linkage Analysis in Outcrossing Polyploids

Creation of linkage maps in polyploid species from marker dosage scores of an F1 cross from two heterozygous parents. Currently works for outcrossing diploid, autotriploid, autotetraploid and autohexaploid species, as well as segmental allotetraploids. Methods are described in a manuscript of Bourke et al. (2018) <doi:10.1093/bioinformatics/bty371>. Since version 1.1.0, both discrete and probabilistic genotypes are acceptable input; for more details on the latter see Liao et al. (2021) <doi:10.1007/s00122-021-03834-x>.

Maintained by Peter Bourke. Last updated 10 months ago.

1 stars 4.03 score 54 scripts

archidart

archiDART:Plant Root System Architecture Analysis Using DART and RSML Files

Analysis of complex plant root system architectures (RSA) using the output files created by Data Analysis of Root Tracings (DART), an open-access software dedicated to the study of plant root architecture and development across time series (Le Bot et al (2010) "DART: a software to analyse root system architecture and development from captured images", Plant and Soil, <DOI:10.1007/s11104-009-0005-2>), and RSA data encoded with the Root System Markup Language (RSML) (Lobet et al (2015) "Root System Markup Language: toward a unified root architecture description language", Plant Physiology, <DOI:10.1104/pp.114.253625>). More information can be found in Delory et al (2016) "archiDART: an R package for the automated computation of plant root architectural traits", Plant and Soil, <DOI:10.1007/s11104-015-2673-4>.

Maintained by Benjamin M Delory. Last updated 4 years ago.

2 stars 4.02 score 13 scripts

stla

jacobi:Jacobi Theta Functions and Related Functions

Evaluation of the Jacobi theta functions and related functions: Weierstrass elliptic function, Weierstrass sigma function, Weierstrass zeta function, Klein j-function, Dedekind eta function, lambda modular function, Jacobi elliptic functions, Neville theta functions, Eisenstein series, lemniscate elliptic functions, elliptic alpha function, Rogers-Ramanujan continued fractions, and Dixon elliptic functions. Complex values of the variable are supported.

Maintained by Stéphane Laurent. Last updated 1 years ago.

elliptic-functions theta-functions cpp

2 stars 4.01 score 103 scripts

bioc

TTMap:Two-Tier Mapper: a clustering tool based on topological data analysis

TTMap is a clustering method that groups together samples with the same deviation in comparison to a control group. It is specially useful when the data is small. It is parameter free.

Maintained by Rachel Jeitziner. Last updated 5 months ago.

software microarray differentialexpression multiplecomparison clustering classification

4.00 score

bioc

OMICsPCA:An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

OMICsPCA is an analysis pipeline designed to integrate multi OMICs experiments done on various subjects (e.g. Cell lines, individuals), treatments (e.g. disease/control) or time points and to analyse such integrated data from various various angles and perspectives. In it's core OMICsPCA uses Principal Component Analysis (PCA) to integrate multiomics experiments from various sources and thus has ability to over data insufficiency issues by using the ingegrated data as representatives. OMICsPCA can be used in various application including analysis of overall distribution of OMICs assays across various samples /individuals /time points; grouping assays by user-defined conditions; identification of source of variation, similarity/dissimilarity between assays, variables or individuals.

Maintained by Subhadeep Das. Last updated 5 months ago.

immunooncology multiplecomparison principalcomponent datarepresentation workflow visualization dimensionreduction clustering biologicalquestion epigeneticsworkflow transcription geneticvariability gui biomedicalinformatics epigenetics functionalgenomics singlecell

4.00 score 1 scripts

raeesaganey91

prinsurf:Constructs Principal Surfaces

Construct a principal surface that are two-dimensional surfaces that pass through the middle of a p-dimensional data set. They minimise the distance from the data points, and provide a nonlinear summary of data. The surfaces are nonparametric and their shape is suggested by the data. The formation of a surface is found using an iterative procedure which starts with a linear summary, typically with a principal component plane. Each successive iteration is a local average of the p-dimensional points, where an average is based on a projection of a point onto the nonlinear surface of the previous iteration. For more information on principal surfaces, see Ganey, R. 2019, Biplots based on principal surfaces,Faculty of Science ,Department of Statistical Sciences, UCT.

Maintained by Raeesa Ganey. Last updated 23 days ago.

4.00 score

antdambr

ConsRank:Compute the Median Ranking(s) According to the Kemeny's Axiomatic Approach

Compute the median ranking according to the Kemeny's axiomatic approach. Rankings can or cannot contain ties, rankings can be both complete or incomplete. The package contains both branch-and-bound algorithms and heuristic solutions recently proposed. The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties. The package also provide some useful utilities for deal with preference rankings, including both element-weight Kemeny distance and correlation coefficient. This release declare as deprecated some functions that are still in the package for compatibility. Next release will not contains these functions. Please type '?ConsRank-deprecated' Essential references: Emond, E.J., and Mason, D.W. (2002) <doi:10.1002/mcda.313>; D'Ambrosio, A., Amodio, S., and Iorio, C. (2015) <doi:10.1285/i20705948v8n2p198>; Amodio, S., D'Ambrosio, A., and Siciliano R. (2016) <doi:10.1016/j.ejor.2015.08.048>; D'Ambrosio, A., Mazzeo, G., Iorio, C., and Siciliano, R. (2017) <doi:10.1016/j.cor.2017.01.017>; Albano, A., and Plaia, A. (2021) <doi:10.1285/i20705948v14n1p117>.

Maintained by Antonio DAmbrosio. Last updated 1 years ago.

3 stars 3.97 score 24 scripts 8 dependents

draalmeida

leafR:Calculates the Leaf Area Index (LAD) and Other Related Functions

A set of functions for analyzing the structure of forests based on the leaf area density (LAD) and leaf area index (LAI) measures calculated from Airborne Laser Scanning (ALS), i.e., scanning lidar (Light Detection and Ranging) data. The methodology is discussed and described in Almeida et al. (2019) <doi:10.3390/rs11010092> and Stark et al. (2012) <doi:10.1111/j.1461-0248.2012.01864.x>.

Maintained by Danilo Roberti Alves de Almeida. Last updated 4 years ago.

17 stars 3.93 score 4 scripts

thebrisklab

SparseICA:Sparse Independent Component Analysis

Provides an implementation of the Sparse ICA method in Wang et al. (2024) <doi:10.1080/01621459.2024.2370593> for estimating sparse independent source components of cortical surface functional MRI data, by addressing a non-smooth, non-convex optimization problem through the relax-and-split framework. This method effectively balances statistical independence and sparsity while maintaining computational efficiency.

Maintained by Zihang Wang. Last updated 2 months ago.

openblas cpp

3 stars 3.88 score

psolymos

EDMAinR:Euclidean Distance Matrix Analysis in R

A coordinate-free approach for comparing biological shapes using landmark data based on Lele and Richtsmeier (1991) <doi:10.1002/ajpa.1330860307>.

Maintained by Peter Solymos. Last updated 2 years ago.

comparing-biological-shapes coordinate-free landmark-data morphometrics multivariate-statistics

3 stars 3.78 score 9 scripts

hypertidy

textures:Plot 3D Textures as 2D Graphics (Kinda)

Illustrate the use of texture mapping in rgl for depicting images in graphics or spatial coordinate systems, and mapped onto arbitrary shapes.

Maintained by Michael D. Sumner. Last updated 2 years ago.

cpp

12 stars 3.78 score 8 scripts

cran

fastml:Fast Machine Learning Model Training and Evaluation

Streamlines the training, evaluation, and comparison of multiple machine learning models with minimal code by providing comprehensive data preprocessing and support for a wide range of algorithms with hyperparameter tuning. It offers performance metrics and visualization tools to facilitate efficient and effective machine learning workflows.

Maintained by Selcuk Korkmaz. Last updated 23 days ago.

3.76 score

eleonoraarnone

fdaPDE:Physics-Informed Spatial and Functional Data Analysis

An implementation of regression models with partial differential regularizations, making use of the Finite Element Method. The models efficiently handle data distributed over irregularly shaped domains and can comply with various conditions at the boundaries of the domain. A priori information about the spatial structure of the phenomenon under study can be incorporated in the model via the differential regularization. See Sangalli, L. M. (2021) <doi:10.1111/insr.12444> "Spatial Regression With Partial Differential Equation Regularisation" for an overview. The release 1.1-9 requires R (>= 4.2.0) to be installed on windows machines.

Maintained by Eleonora Arnone. Last updated 3 months ago.

cpp

1 stars 3.73 score 267 scripts

erichare

bulletr:Algorithms for Matching Bullet Lands

Analyze bullet lands using nonparametric methods. We provide a reading routine for x3p files (see <http://www.openfmc.org> for more information) and a host of analysis functions designed to assess the probability that two bullets were fired from the same gun barrel.

Maintained by Eric Hare. Last updated 7 years ago.

3.72 score 52 scripts

sharifrahmanie

MBMethPred:Medulloblastoma Subgroups Prediction

Utilizing a combination of machine learning models (Random Forest, Naive Bayes, K-Nearest Neighbor, Support Vector Machines, Extreme Gradient Boosting, and Linear Discriminant Analysis) and a deep Artificial Neural Network model, 'MBMethPred' can predict medulloblastoma subgroups, including wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 from DNA methylation beta values. See Sharif Rahmani E, Lawarde A, Lingasamy P, Moreno SV, Salumets A and Modhukur V (2023), MBMethPred: a computational framework for the accurate classification of childhood medulloblastoma subgroups using data integration and AI-based approaches. Front. Genet. 14:1233657. <doi: 10.3389/fgene.2023.1233657> for more details.

Maintained by Edris Sharif Rahmani. Last updated 2 years ago.

3.70 score 1 scripts

billbillbilly

dsmSearch:DSM and LiDAR downloader

A collection of functions to search and donwload DSM (Digital Surface Model) and LiDAR (Light Detection and Ranging) data via APIs, including 'OpenTopography' <https://portal.opentopography.org/apidocs/> and 'TNMAccess' <https://apps.nationalmap.gov/tnmaccess/#/>.

Maintained by Xiaohao Yang. Last updated 11 months ago.

1 stars 3.70 score

stla

polyhedralCubature:Multiple Integration over Convex Polyhedra

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

Maintained by Stéphane Laurent. Last updated 1 years ago.

integration multidimensional-integration

3.70 score 4 scripts

kisungyou

Riemann:Learning with Data on Riemannian Manifolds

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

Maintained by Kisung You. Last updated 2 years ago.

openblas cpp openmp

10 stars 3.70 score 8 scripts

jamesramsay5

SpatialfdaR:Spatial Functional Data Analysis

Finite element modeling (FEM) uses meshes of triangles to define surfaces. A surface within a triangle may be either linear or quadratic. In the order one case each node in the mesh is associated with a basis function and the basis is called the order one finite element basis. In the order two case each edge mid-point is also associated with a basis function. Functions are provided for smoothing, density function estimation point evaluation and plotting results. Two papers illustrating the finite element data analysis are Sangalli, L.M., Ramsay, J.O., Ramsay, T.O. (2013)<http://www.mox.polimi.it/~sangalli> and Bernardi, M.S, Carey, M., Ramsay, J. O., Sangalli, L. (2018)<http://www.mox.polimi.it/~sangalli>. Modelling spatial anisotropy via regression with partial differential regularization Journal of Multivariate Analysis, 167, 15-30.

Maintained by James Ramsay. Last updated 2 years ago.

3.70 score 2 scripts

vic-dragon

dmri.tracking:DiST - Diffusion Direction Smoothing and Tracking

It provides functions to apply the deterministic tracking algorithm - DiST (Wong et al 2016) <doi:10.1214/15-AOAS880> and to plot tractography results.

Maintained by Seungyong Hwang. Last updated 4 years ago.

1 stars 3.70 score 3 scripts

kangjian2016

brainKCCA:Region-Level Connectivity Network Construction via Kernel Canonical Correlation Analysis

It is designed to calculate connection between (among) brain regions and plot connection lines. Also, the summary function is included to summarize group-level connectivity network. Kang, Jian (2016) <doi:10.1016/j.neuroimage.2016.06.042>.

Maintained by Jian Kang. Last updated 6 years ago.

3.70 score 5 scripts

gastonmaurodiaz

rcaiman:CAnopy IMage ANalysis

Tools for pre-processing and processing canopy photographs with support for raw data reading. Works with images taken with both regular and fisheye lenses (all types). Includes algorithms specifically designed to mitigate errors caused by direct sunlight.

Maintained by Gastón Mauro Díaz. Last updated 1 days ago.

1 stars 3.65 score 2 scripts

promidat

traineR:Predictive (Classification and Regression) Models Homologator

Methods to unify the different ways of creating predictive models and their different predictive formats for classification and regression. It includes methods such as K-Nearest Neighbors Schliep, K. P. (2004) <doi:10.5282/ubm/epub.1769>, Decision Trees Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone (2017) <doi:10.1201/9781315139470>, ADA Boosting Esteban Alfaro, Matias Gamez, Noelia García (2013) <doi:10.18637/jss.v054.i02>, Extreme Gradient Boosting Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>, Random Forest Breiman (2001) <doi:10.1023/A:1010933404324>, Neural Networks Venables, W. N., & Ripley, B. D. (2002) <ISBN:0-387-95457-0>, Support Vector Machines Bennett, K. P. & Campbell, C. (2000) <doi:10.1145/380995.380999>, Bayesian Methods Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (1995) <doi:10.1201/9780429258411>, Linear Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) <ISBN:0-387-95457-0>, Quadratic Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) <ISBN:0-387-95457-0>, Logistic Regression Dobson, A. J., & Barnett, A. G. (2018) <doi:10.1201/9781315182780> and Penalized Logistic Regression Friedman, J. H., Hastie, T., & Tibshirani, R. (2010) <doi:10.18637/jss.v033.i01>.

Maintained by Oldemar Rodriguez R.. Last updated 1 years ago.

3.64 score 36 scripts 2 dependents

cran

optiSel:Optimum Contribution Selection and Population Genetics

A framework for the optimization of breeding programs via optimum contribution selection and mate allocation. An easy to use set of function for computation of optimum contributions of selection candidates, and of the population genetic parameters to be optimized. These parameters can be estimated using pedigree or genotype information, and include kinships, kinships at native haplotype segments, and breed composition of crossbred individuals. They are suitable for managing genetic diversity, removing introgressed genetic material, and accelerating genetic gain. Additionally, functions are provided for computing genetic contributions from ancestors, inbreeding coefficients, the native effective size, the native genome equivalent, pedigree completeness, and for preparing and plotting pedigrees. The methods are described in:\n Wellmann, R., and Pfeiffer, I. (2009) <doi:10.1017/S0016672309000202>.\n Wellmann, R., and Bennewitz, J. (2011) <doi:10.2527/jas.2010-3709>.\n Wellmann, R., Hartwig, S., Bennewitz, J. (2012) <doi:10.1186/1297-9686-44-34>.\n de Cara, M. A. R., Villanueva, B., Toro, M. A., Fernandez, J. (2013) <doi:10.1111/mec.12560>.\n Wellmann, R., Bennewitz, J., Meuwissen, T.H.E. (2014) <doi:10.1017/S0016672314000196>.\n Wellmann, R. (2019) <doi:10.1186/s12859-018-2450-5>.

Maintained by Robin Wellmann. Last updated 9 months ago.

cpp

1 stars 3.62 score

karlines

plot3Drgl:Plotting Multi-Dimensional Data - Using 'rgl'

The 'rgl' implementation of plot3D functions.

Maintained by Karline Soetaert. Last updated 2 years ago.

3.62 score 133 scripts 5 dependents

christophe314

kml:K-Means for Longitudinal Data

An implementation of k-means specifically design to cluster longitudinal data. It provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical interface for choosing the 'best' number of clusters.

Maintained by Christophe Genolini. Last updated 5 months ago.

3.57 score 110 scripts 1 dependents

christophe314

longitudinalData:Longitudinal Data

Tools for longitudinal data and joint longitudinal data (used by packages kml and kml3d).

Maintained by Christophe Genolini. Last updated 6 months ago.

1 stars 3.55 score 65 scripts 11 dependents

mohsentaherishalmani

ETRep:Analysis of Elliptical Tubes Under the Relative Curvature Condition

Analysis of elliptical tubes with applications in biological modeling. The package is based on the references: Taheri, M., Pizer, S. M., & Schulz, J. (2024) "The Mean Shape under the Relative Curvature Condition." arXiv <doi:10.48550/arXiv.2404.01043>. Mohsen Taheri Shalmani (2024) "Shape Statistics via Skeletal Structures", PhD Thesis, University of Stavanger, Norway <doi:10.13140/RG.2.2.34500.23685>. Key features include constructing discrete elliptical tubes, calculating transformations, validating structures under the Relative Curvature Condition (RCC), computing means, and generating simulations. Supports intrinsic and non-intrinsic mean calculations and transformations, size estimation, plotting, and random sample generation based on a reference tube. The intrinsic approach relies on the interior path of the original non-convex space, incorporating the RCC, while the non-intrinsic approach uses a basic robotic arm transformation that disregards the RCC.

Maintained by Mohsen Taheri Shalmani. Last updated 3 months ago.

3.54 score 3 scripts

asgr

sphereplot:Spherical Plotting

Various functions for creating spherical coordinate system plots via extensions to rgl.

Maintained by Aaron Robotham. Last updated 2 years ago.

3 stars 3.52 score 37 scripts 1 dependents

barnhilldave

TML:Tropical Geometry Tools for Machine Learning

Suite of tropical geometric tools for use in machine learning applications. These methods may be summarized in the following references: Yoshida, et al. (2022) <arxiv:2209.15045>, Barnhill et al. (2023) <arxiv:2303.02539>, Barnhill and Yoshida (2023) <doi:10.3390/math11153433>, Aliatimis et al. (2023) <arXiv:2306.08796>, Yoshida et al. (2022) <arXiv:2206.04206>, and Yoshida et al. (2019) <doi:10.1007/s11538-018-0493-4>.

Maintained by David Barnhill. Last updated 8 months ago.

3 stars 3.48 score 1 scripts

toduckhanh

bcROCsurface:Bias-Corrected Methods for Estimating the ROC Surface of Continuous Diagnostic Tests

The bias-corrected estimation methods for the receiver operating characteristics ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) assumption.

Maintained by Duc-Khanh To. Last updated 1 years ago.

openblas cpp

3.45 score 14 scripts

bioc

fCI:f-divergence Cutoff Index for Differential Expression Analysis in Transcriptomics and Proteomics

(f-divergence Cutoff Index), is to find DEGs in the transcriptomic & proteomic data, and identify DEGs by computing the difference between the distribution of fold-changes for the control-control and remaining (non-differential) case-control gene expression ratio data. fCI provides several advantages compared to existing methods.

Maintained by Shaojun Tang. Last updated 5 months ago.

proteomics

3.30 score 5 scripts

mikelkou

ucie:Mapping 3D Data into CIELab Color Space

Returns a data frame with the names of the input data points and hex colors (or CIELab coordinates). Data can be mapped to colors for use in data visualization. It optimally maps data points into a polygon that represents the CIELab colour space. Since Euclidean distance approximates relative perceptual differences in CIELab color space, the result is a color encoding that aims to capture much of the structure of the original data.

Maintained by Mikaela Koutrouli. Last updated 2 years ago.

4 stars 3.30 score 6 scripts

havishaj

Greymodels:Shiny App for Grey Forecasting Model

The 'Greymodels' Shiny app is an interactive interface for statistical modelling and forecasting using grey-based models. It covers several state-of-the-art univariate and multivariate grey models. A user friendly interface allows users to easily compare the performance of different models for prediction and among others, visualize graphical plots of predicted values within user chosen confidence intervals. Chang, C. (2019) <doi:10.24818/18423264/53.1.19.11>, Li, K., Zhang, T. (2019) <doi:10.1007/s12667-019-00344-0>, Ou, S. (2012) <doi:10.1016/j.compag.2012.03.007>, Li, S., Zhou, M., Meng, W., Zhou, W. (2019) <doi:10.1080/23307706.2019.1666310>, Xie, N., Liu, S. (2009) <doi:10.1016/j.apm.2008.01.011>, Shao, Y., Su, H. (2012) <doi:10.1016/j.aasri.2012.06.003>, Xie, N., Liu, S., Yang, Y., Yuan, C. (2013) <doi:10.1016/j.apm.2012.10.037>, Li, S., Miao, Y., Li, G., Ikram, M. (2020) <doi:10.1016/j.matcom.2019.12.020>, Che, X., Luo, Y., He, Z. (2013) <doi:10.4028/www.scientific.net/AMM.364.207>, Zhu, J., Xu, Y., Leng, H., Tang, H., Gong, H., Zhang, Z. (2016) <doi:10.1109/appeec.2016.7779929>, Luo, Y., Liao, D. (2012) <doi:10.4028/www.scientific.net/AMR.507.265>, Bilgil, H. (2020) <doi:10.3934/math.2021091>, Li, D., Chang, C., Chen, W., Chen, C. (2011) <doi:10.1016/j.apm.2011.04.006>, Chen, C. (2008) <doi:10.1016/j.chaos.2006.08.024>, Zhou, W., Pei, L. (2020) <doi:10.1007/s00500-019-04248-0>, Xiao, X., Duan, H. (2020) <doi:10.1016/j.engappai.2019.103350>, Xu, N., Dang, Y. (2015) <doi:10.1155/2015/606707>, Chen, P., Yu, H.(2014) <doi:10.1155/2014/242809>, Zeng, B., Li, S., Meng, W., Zhang, D. (2019) <doi:10.1371/journal.pone.0221333>, Liu, L., Wu, L. (2021) <doi:10.1016/j.apm.2020.08.080>, Hu, Y. (2020) <doi:10.1007/s00500-020-04765-3>, Zhou, P., Ang, B., Poh, K. (2006) <doi:10.1016/j.energy.2005.12.002>, Cheng, M., Li, J., Liu, Y., Liu, B. (2020) <doi:10.3390/su12020698>, Wang, H., Wang, P., Senel, M., Li, T. (2019) <doi:10.1155/2019/9049815>, Ding, S., Li, R. (2020) <doi:10.1155/2020/4564653>, Zeng, B., Li, C. (2018) <doi:10.1016/j.cie.2018.02.042>, Xie, N., Liu, S. (2015) <doi:10.1109/JSEE.2015.00013>, Zeng, X., Yan, S., He, F., Shi, Y. (2019) <doi:10.1016/j.apm.2019.11.032>.

Maintained by Jahajeeah Havisha. Last updated 2 years ago.

4 stars 3.30 score

bioc

optimalFlow:optimalFlow

Optimal-transport techniques applied to supervised flow cytometry gating.

Maintained by Hristo Inouzhe. Last updated 5 months ago.

software flowcytometry technology

3.30 score 1 scripts

zijguo

controlfunctionIV:Control Function Methods with Possibly Invalid Instrumental Variables

Inference with control function methods for nonlinear outcome models when the model is known ('Guo and Small' (2016) <arXiv:1602.01051>) and when unknown but semiparametric ('Li and Guo' (2021) <arXiv:2010.09922>).

Maintained by Zijian Guo. Last updated 3 years ago.

4 stars 3.30 score 1 scripts

bioc

clippda:A package for the clinical proteomic profiling data analysis

Methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations.

Maintained by Stephen Nyangoma. Last updated 5 months ago.

proteomics onechannel preprocessing differentialexpression multiplecomparison

3.30 score 2 scripts

cran

ashapesampler:Generating Alpha Shapes

Understanding morphological variation is an important task in many applications. Recent studies in computational biology have focused on developing computational tools for the task of sub-image selection which aims at identifying structural features that best describe the variation between classes of shapes. A major part in assessing the utility of these approaches is to demonstrate their performance on both simulated and real datasets. However, when creating a model for shape statistics, real data can be difficult to access and the sample sizes for these data are often small due to them being expensive to collect. Meanwhile, the landscape of current shape simulation methods has been mostly limited to approaches that use black-box inference---making it difficult to systematically assess the power and calibration of sub-image models. In this R package, we introduce the alpha-shape sampler: a probabilistic framework for simulating realistic 2D and 3D shapes based on probability distributions which can be learned from real data or explicitly stated by the user. The 'ashapesampler' package supports two mechanisms for sampling shapes in two and three dimensions. The first, empirically sampling based on an existing data set, was highlighted in the original main text of the paper. The second, probabilistic sampling from a known distribution, is the computational implementation of the theory derived in that paper. Work based on Winn-Nunez et al. (2024) <doi:10.1101/2024.01.09.574919>.

Maintained by Emily Winn-Nunez. Last updated 1 years ago.

3.30 score

fguenther

LSAfun:Applied Latent Semantic Analysis (LSA) Functions

Provides functions that allow for convenient working with vector space models of semantics/distributional semantic models/word embeddings. Originally built for LSA models (hence the name), but can be used for all such vector-based models. For actually building a vector semantic space, use the package 'lsa' or other specialized software. Downloadable semantic spaces can be found at <https://sites.google.com/site/fritzgntr/software-resources>.

Maintained by Fritz Guenther. Last updated 1 years ago.

1 stars 3.18 score 85 scripts 1 dependents

stla

Apollonius:2D Apollonius Graphs

Computation of the Apollonius diagram of given 2D points and its dual the Apollonius graph, also known as the additively weighted Voronoï diagram, and which is a generalization of the classical Voronoï diagram. For references, see the bibliography in the CGAL documentation at <https://doc.cgal.org/latest/Apollonius_graph_2/citelist.html>.

Maintained by Stéphane Laurent. Last updated 1 years ago.

cgal computational-geometry rcpp voronoi-diagram gmp cpp

3 stars 3.18 score 5 scripts

pakillo

CityShadeMapper:Generate High Resolution Shade Maps and Shaded Routes from Remote Sensing Data

CityShadeMapper can generate high resolution shade maps (e.g. for every square meter and every hour of the year) for any city or town from open remote sensing (LiDAR) data. CityShadeMapper can also return optimal routes within any two points in the city that maximise the amount of shade for pedestrians.

Maintained by Francisco Rodríguez-Sánchez. Last updated 1 years ago.

gis lidar urban-data-science urban-planning

25 stars 3.10 score 3 scripts

cran

MDSMap:High Density Genetic Linkage Mapping using Multidimensional Scaling

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

Maintained by Bram Boskamp. Last updated 7 years ago.

3.08 score 1 dependents

cran

qpcR:Modelling and Analysis of Real-Time PCR Data

Model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).

Maintained by Andrej-Nikolai Spiess. Last updated 7 years ago.

2 stars 3.06 score 1 dependents

auroreaa

ICSClust:Tandem Clustering with Invariant Coordinate Selection

Implementation of tandem clustering with invariant coordinate selection with different scatter matrices and several choices for the selection of components as described in Alfons, A., Archimbaud, A., Nordhausen, K.and Ruiz-Gazen, A. (2022) <arXiv:2212.06108>.

Maintained by Aurore Archimbaud. Last updated 2 years ago.

openblas cpp

3.04 score 11 scripts

epertham

xLLiM:High Dimensional Locally-Linear Mapping

Provides a tool for non linear mapping (non linear regression) using a mixture of regression model and an inverse regression strategy. The methods include the GLLiM model (see Deleforge et al (2015) <DOI:10.1007/s11222-014-9461-5>) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) <DOI:10.1016/j.jmva.2017.09.009>) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Devijver et al (2017) <arXiv:1701.07899>) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).

Maintained by Emeline Perthame. Last updated 1 years ago.

mixomics

1 stars 3.02 score 21 scripts

asgr

hyper.fit:N-Dimensional Hyperplane Fitting with Errors

High level functions for hyperplane fitting (hyper.fit()) and visualising (hyper.plot2d() / hyper.plot3d()). In simple terms this allows the user to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimension dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane.

Maintained by Aaron Robotham. Last updated 10 months ago.

7 stars 3.02 score 15 scripts

mondrus96

fabisearch:Change Point Detection in High-Dimensional Time Series Networks

Implementation of the Factorized Binary Search (FaBiSearch) methodology for the estimation of the number and the location of multiple change points in the network (or clustering) structure of multivariate high-dimensional time series. The method is motivated by the detection of change points in functional connectivity networks for functional magnetic resonance imaging (fMRI) data. FaBiSearch uses non-negative matrix factorization (NMF), an unsupervised dimension reduction technique, and a new binary search algorithm to identify multiple change points. It requires minimal assumptions. Lastly, we provide interactive, 3-dimensional, brain-specific network visualization capability in a flexible, stand-alone function. This function can be conveniently used with any node coordinate atlas, and nodes can be color coded according to community membership, if applicable. The output is an elegantly displayed network laid over a cortical surface, which can be rotated in the 3-dimensional space. The main routines of the package are detect.cps(), for multiple change point detection, est.net(), for estimating a network between stationary multivariate time series, net.3dplot(), for plotting the estimated functional connectivity networks, and opt.rank(), for finding the optimal rank in NMF for a given data set. The functions have been extensively tested on simulated multivariate high-dimensional time series data and fMRI data. For details on the FaBiSearch methodology, please see Ondrus et al. (2021) <arXiv:2103.06347>. For a more detailed explanation and applied examples of the fabisearch package, please see Ondrus and Cribben (2022), preprint.

Maintained by Martin Ondrus. Last updated 7 months ago.

1 stars 3.00 score 2 scripts

bioc

iCheck:QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data

QC pipeline and data analysis tools for high-dimensional Illumina mRNA expression data.

Maintained by Weiliang Qiu. Last updated 5 months ago.

geneexpression differentialexpression microarray preprocessing dnamethylation onechannel twochannel qualitycontrol

3.00 score 1 scripts

z267xu

vennplot:Venn Diagrams in 2D and 3D

Calculate and plot Venn diagrams in 2D and 3D.

Maintained by Zehao Xu. Last updated 7 years ago.

cpp

2 stars 3.00 score 3 scripts

bioc

traviz:Trajectory functions for visualization and interpretation.

traviz provides a suite of functions to plot trajectory related objects from Bioconductor packages. It allows plotting trajectories in reduced dimension, as well as averge gene expression smoothers as a function of pseudotime. Asides from general utility functions, traviz also allows plotting trajectories estimated by Slingshot, as well as smoothers estimated by tradeSeq. Furthermore, it allows for visualization of Slingshot trajectories using ggplot2.

Maintained by Koen Van den Berge. Last updated 5 months ago.

geneexpression rnaseq sequencing software singlecell transcriptomics visualization

3.00 score 2 scripts

mbeauvai

AFM:Atomic Force Microscope Image Analysis

Provides Atomic Force Microscope images analysis such as Gaussian mixes identification, Power Spectral Density, roughness against lengthscale, experimental variogram and variogram models, fractal dimension and scale, 2D network analysis. The AFM images can be exported to STL format for 3D printing.

Maintained by Mathieu Beauvais. Last updated 4 years ago.

1 stars 2.96 score 92 scripts

cran

MultivariateAnalysis:Pacote Para Analise Multivariada

Package with multivariate analysis methodologies for experiment evaluation. The package estimates dissimilarity measures, builds dendrograms, obtains MANOVA, principal components, canonical variables, etc. (Pacote com metodologias de analise multivariada para avaliação de experimentos. O pacote estima medidas de dissimilaridade, construi de dendogramas, obtem a MANOVA, componentes principais, variaveis canonicas, etc.)

Maintained by Alcinei Mistico Azevedo. Last updated 12 months ago.

2.95 score

elvanceyhan

nnspat:Nearest Neighbor Methods for Spatial Patterns

Contains the functions for testing the spatial patterns (of segregation, spatial symmetry, association, disease clustering, species correspondence and reflexivity) based on nearest neighbor relations, especially using contingency tables such as nearest neighbor contingency tables (Ceyhan (2010) <doi:10.1007/s10651-008-0104-x> and Ceyhan (2017) <doi:10.1016/j.jkss.2016.10.002> and references therein), nearest neighbor symmetry contingency tables (Ceyhan (2014) <doi:10.1155/2014/698296>), species correspondence contingency tables and reflexivity contingency tables (Ceyhan (2018) <doi:10.2436/20.8080.02.72>) for two (or higher) dimensional data. Also contains functions for generating patterns of segregation, association, uniformity in a multi-class setting (Ceyhan (2014) <doi:10.1007/s00477-013-0824-9>), and various non-random labeling patterns for disease clustering in two dimensional cases (Ceyhan (2014) <doi:10.1002/sim.6053>), and for visualization of all these patterns for the two dimensional data. The tests are usually (asymptotic) normal z-tests and chi-square tests.

Maintained by Elvan Ceyhan. Last updated 3 years ago.

2.90 score 16 scripts

cran

GPoM:Generalized Polynomial Modelling

Platform dedicated to the Global Modelling technique. Its aim is to obtain ordinary differential equations of polynomial form directly from time series. It can be applied to single or multiple time series under various conditions of noise, time series lengths, sampling, etc. This platform is developped at the Centre d'Etudes Spatiales de la Biosphere (CESBIO), UMR 5126 UPS/CNRS/CNES/IRD, 18 av. Edouard Belin, 31401 TOULOUSE, FRANCE. The developments were funded by the French program Les Enveloppes Fluides et l'Environnement (LEFE, MANU, projets GloMo, SpatioGloMo and MoMu). The French program Defi InFiNiTi (CNRS) and PNTS are also acknowledged (projects Crops'IChaos and Musc & SlowFast). The method is described in the article : Mangiarotti S. and Huc M. (2019) <doi:10.1063/1.5081448>.

Maintained by Mireille Huc. Last updated 2 years ago.

2.90 score

adafede

sapid:A Strategy to Analyze Plant Extracts Taste In Depth

This package provides the infrastructure to implement a Strategy to Analyze Plant Extracts Taste In Depth.

Maintained by Adriano Rutz. Last updated 3 days ago.

computational metabolomics natural extracts taste

2.90 score

cran

TSdist:Distance Measures for Time Series Data

A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series. U. Mori, A. Mendiburu and J.A. Lozano (2016), <doi:10.32614/RJ-2016-058>.

Maintained by Usue Mori. Last updated 3 years ago.

5 stars 2.88 score 5 dependents

radivot

SEERaBomb:SEER and Atomic Bomb Survivor Data Analysis Tools

Creates SEER (Surveillance, Epidemiology and End Results) and A-bomb data binaries from ASCII sources and provides tools for estimating SEER second cancer risks. Methods are described in <doi:10.1038/leu.2015.258>.

Maintained by Tomas Radivoyevitch. Last updated 5 years ago.

cpp

2.85 score 176 scripts

cran

espadon:Easy Study of Patient DICOM Data in Oncology

Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.

Maintained by Cathy Fontbonne. Last updated 2 months ago.

cpp

2.85 score

shulele

RoundAndRound:Plot Objects Moving in Orbits

Visualize the objects in orbits in 2D and 3D. The packages is under developing to plot the orbits of objects in polar coordinate system. See the examples in demo.

Maintained by Lele Shu. Last updated 5 years ago.

2.81 score 13 scripts

cran

mixKernel:Omics Data Integration Using Kernel Methods

Kernel-based methods are powerful methods for integrating heterogeneous types of data. mixKernel aims at providing methods to combine kernel for unsupervised exploratory analysis. Different solutions are provided to compute a meta-kernel, in a consensus way or in a way that best preserves the original topology of the data. mixKernel also integrates kernel PCA to visualize similarities between samples in a non linear space and from the multiple source point of view <doi:10.1093/bioinformatics/btx682>. A method to select (as well as funtions to display) important variables is also provided <doi:10.1093/nargab/lqac014>.

Maintained by Nathalie Vialaneix. Last updated 1 years ago.

2.78 score

cran

Anthropometry:Statistical Methods for Anthropometric Data

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.

Maintained by Guillermo Vinue. Last updated 2 years ago.

1 stars 2.78 score 2 dependents

cran

stpp:Space-Time Point Pattern Simulation, Visualisation and Analysis

Many of the models encountered in applications of point process methods to the study of spatio-temporal phenomena are covered in 'stpp'. This package provides statistical tools for analyzing the global and local second-order properties of spatio-temporal point processes, including estimators of the space-time inhomogeneous K-function and pair correlation function. It also includes tools to get static and dynamic display of spatio-temporal point patterns. See Gabriel et al (2013) <doi:10.18637/jss.v053.i02>.

Maintained by Edith Gabriel. Last updated 9 months ago.

fortran

2 stars 2.78 score 1 dependents

cran

RPointCloud:Visualizing Topological Loops and Voids

Visualizations to explain the results of a topological data analysis. The goal of topological data analysis is to identify persistent topological structures, such as loops (topological circles) and voids (topological spheres), in data sets. The output of an analysis using the 'TDA' package is a Rips diagram (named after the mathematician Eliyahu Rips). The goal of 'RPointCloud' is to fill in these holes in the data by providing tools to visualize the features that help explain the structures found in the Rips diagram. See McGee and colleagues (2024) <doi:10.1101/2024.05.16.593927>.

Maintained by Kevin R. Coombes. Last updated 7 months ago.

2.78 score

elvanceyhan

pcds.ugraph:Underlying Graphs of Proximity Catch Digraphs and Their Applications

Contains the functions for construction and visualization of underlying and reflexivity graphs of the three families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2), and for computing the edge density of these PCD-based graphs which are then used for testing the patterns of segregation and association against complete spatial randomness (CSR)) or uniformity in one and two dimensional cases. The PCD families considered are Arc-Slice PCDs, Proportional-Edge (PE) PCDs (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>) and Central Similarity PCDs (Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). See also (Ceyhan (2016) <doi:10.1016/j.stamet.2016.07.003> for edge density of the underlying and reflexivity graphs of PE-PCDs. The package also has tools for visualization of PCD-based graphs for one, two, and three dimensional data.

Maintained by Elvan Ceyhan. Last updated 2 years ago.

2.70 score

rikenbit

mwTensor:Multi-Way Component Analysis

For single tensor data, any matrix factorization method can be specified the matricised tensor in each dimension by Multi-way Component Analysis (MWCA). An originally extended MWCA is also implemented to specify and decompose multiple matrices and tensors simultaneously (CoupledMWCA). See the reference section of GitHub README.md <https://github.com/rikenbit/mwTensor>, for details of the methods.

Maintained by Koki Tsuyuzaki. Last updated 2 years ago.

2.70 score 2 scripts

cran

trinROC:Statistical Tests for Assessing Trinormal ROC Data

Several statistical test functions as well as a function for exploratory data analysis to investigate classifiers allocating individuals to one of three disjoint and ordered classes. In a single classifier assessment the discriminatory power is compared to classification by chance. In a comparison of two classifiers the null hypothesis corresponds to equal discriminatory power of the two classifiers. See also "ROC Analysis for Classification and Prediction in Practice" by Nakas, Bantis and Gatsonis (2023), ISBN 9781482233704.

Maintained by Reinhard Furrer. Last updated 6 months ago.

2.70 score

jamesramsay5

TestGardener:Information Analysis for Test and Rating Scale Data

Develop, evaluate, and score multiple choice examinations, psychological scales, questionnaires, and similar types of data involving sequences of choices among one or more sets of answers. This version of the package should be considered as brand new. Almost all of the functions have been changed, including their argument list. See the file NEWS.Rd in the Inst folder for more information. Using the package does not require any formal statistical knowledge beyond what would be provided by a first course in statistics in a social science department. There the user would encounter the concept of probability and how it is used to model data and make decisions, and would become familiar with basic mathematical and statistical notation. Most of the output is in graphical form.

Maintained by James Ramsay. Last updated 1 years ago.

1 stars 2.70 score 5 scripts

ivanalaman

lba:Latent Budget Analysis for Compositional Data

Latent budget analysis is a method for the analysis of a two-way contingency table with an exploratory variable and a response variable. It is specially designed for compositional data.

Maintained by Ivan Bezerra Allaman. Last updated 2 years ago.

1 stars 2.70 score 10 scripts

nialsig

doolkit:Exploration of Dental Surface Topography

Tools for exploring the topography of 3d triangle meshes. The functions were developed with dental surfaces in mind, but could be applied to any triangle mesh of class 'mesh3d'. More specifically, 'doolkit' allows to isolate the border of a mesh, or a subpart of the mesh using the polygon networks method; crop a mesh; compute basic descriptors (elevation, orientation, footprint area); compute slope, angularity and relief index (Ungar and Williamson (2000) <https://palaeo-electronica.org/2000_1/gorilla/issue1_00.htm>; Boyer (2008) <doi:10.1016/j.jhevol.2008.08.002>), inclination and occlusal relief index or gamma (Guy et al. (2013) <doi:10.1371/journal.pone.0066142>), OPC (Evans et al. (2007) <doi:10.1038/nature05433>), OPCR (Wilson et al. (2012) <doi:10.1038/nature10880>), DNE (Bunn et al. (2011) <doi:10.1002/ajpa.21489>; Pampush et al. (2016) <doi:10.1007/s10914-016-9326-0>), form factor (Horton (1932) <doi:10.1029/TR013i001p00350>), basin elongation (Schum (1956) <doi:10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2>), lemniscate ratio (Chorley et al; (1957) <doi:10.2475/ajs.255.2.138>), enamel-dentine distance (Guy et al. (2015) <doi:10.1371/journal.pone.0138802>; Thiery et al. (2017) <doi:10.3389/fphys.2017.00524>), absolute crown strength (Schwartz et al. (2020) <doi:10.1098/rsbl.2019.0671>), relief rate (Thiery et al. (2019) <doi:10.1002/ajpa.23916>) and area-relative curvature; draw cumulative profiles of a topographic variable; and map a variable over a 3d triangle mesh.

Maintained by Ghislain Thiery. Last updated 1 years ago.

1 stars 2.70 score 1 scripts

cran

TestDimorph:Analysis of the Interpopulation Difference in Degree of Sexual Dimorphism Using Summary Statistics

Offers a solution for the unavailability of raw data in most anthropological studies by facilitating the calculations of several sexual dimorphism related analyses using the published summary statistics of metric data (mean, standard deviation and sex specific sample size) as illustrated by the works of Relethford, J. H., & Hodges, D. C. (1985) <doi:10.1002/ajpa.1330660105>, Greene, D. L. (1989) <doi:10.1002/ajpa.1330790113> and Konigsberg, L. W. (1991) <doi:10.1002/ajpa.1330840110>.

Maintained by Bassam A. Abulnoor. Last updated 1 years ago.

1 stars 2.70 score

jaydevine

pheble:Classifying High-Dimensional Phenotypes with Ensemble Learning

A system for binary and multi-class classification of high-dimensional phenotypic data using ensemble learning. By combining predictions from different classification models, this package attempts to improve performance over individual learners. The pre-processing, training, validation, and testing are performed end-to-end to minimize user input and simplify the process of classification.

Maintained by Jay Devine. Last updated 2 years ago.

2.70 score

vpicheny

GPGame:Solving Complex Game Problems using Gaussian Processes

Sequential strategies for finding a game equilibrium are proposed in a black-box setting (expensive pay-off evaluations, no derivatives). The algorithm handles noiseless or noisy evaluations. Two acquisition functions are available. Graphical outputs can be generated automatically. V. Picheny, M. Binois, A. Habbal (2018) <doi:10.1007/s10898-018-0688-0>. M. Binois, V. Picheny, P. Taillandier, A. Habbal (2020) <arXiv:1902.06565v2>.

Maintained by Victor Picheny. Last updated 3 years ago.

cpp

2.70 score

toduckhanh

ClusROC:ROC Analysis in Three-Class Classification Problems for Clustered Data

Statistical methods for ROC surface analysis in three-class classification problems for clustered data and in presence of covariates. In particular, the package allows to obtain covariate-specific point and interval estimation for: (i) true class fractions (TCFs) at fixed pairs of thresholds; (ii) the ROC surface; (iii) the volume under ROC surface (VUS); (iv) the optimal pairs of thresholds. Methods considered in points (i), (ii) and (iv) are proposed and discussed in To et al. (2022) <doi:10.1177/09622802221089029>. Referring to point (iv), three different selection criteria are implemented: Generalized Youden Index (GYI), Closest to Perfection (CtP) and Maximum Volume (MV). Methods considered in point (iii) are proposed and discussed in Xiong et al. (2018) <doi:10.1177/0962280217742539>. Visualization tools are also provided. We refer readers to the articles cited above for all details.

Maintained by Duc-Khanh To. Last updated 2 years ago.

biomaker box-cox-transformation mixed-effects-models optimal-threshold reciver-operating-characteristics cpp

2.70 score 6 scripts

daeyounglim

adaptIVPT:Adaptive Bioequivalence Design for In-Vitro Permeation Tests

Contains functions carrying out adaptive procedures using mixed scaling approach to establish bioequivalence for in-vitro permeation test (IVPT) data. Currently, the package provides procedures based on parallel replicate design and balanced data, according to the U.S. Food and Drug Administration's "Draft Guidance on Acyclovir" <https://www.accessdata.fda.gov/drugsatfda_docs/psg/Acyclovir_topical%20cream_RLD%2021478_RV12-16.pdf>. Potvin et al. (2008) <doi:10.1002/pst.294> provides the basis for our adaptive design (see Method B). For a comprehensive overview of the method, refer to Lim et al. (2023) <doi:10.1002/pst.2333>. This package reflects the views of the authors and should not be construed to represent the views or policies of the U.S. Food and Drug Administration.

Maintained by Daeyoung Lim. Last updated 1 years ago.

cpp openmp

2.70 score

stla

concom:Connected Components of an Undirected Graph

Provides a function for fast computation of the connected components of an undirected graph (though not faster than the components() function of the 'igraph' package) from the edges or the adjacency matrix of the graph. Based on this one, a function to compute the connected components of a triangle 'rgl' mesh is also provided.

Maintained by Stéphane Laurent. Last updated 3 years ago.

cpp

1 stars 2.70 score 7 scripts

matt-dray

gpx3d:3D Plot A Route From A GPX File

Extract a data from a GPX file into a an sf-class dataframe, then plot a 3D rendering of the route. Designed with workout-route data from the Apple Health app in mind.

Maintained by Matt Dray. Last updated 3 years ago.

apple-health ggrgl gpx

9 stars 2.65 score

hongyuanjia

epluspar:Conduct Parametric Analysis on 'EnergyPlus' Models

A toolkit for conducting parametric analysis on 'EnergyPlus'(<https://energyplus.net>) models in R, including sensitivity analysis using Morris method and Bayesian calibration using using 'Stan'(<https://mc-stan.org>). References: Chong (2018) <doi:10.1016/j.enbuild.2018.06.028>.

Maintained by Hongyuan Jia. Last updated 1 years ago.

bayesian-calibration energyplus parametric sensitivity-analysis cpp

9 stars 2.65 score 4 scripts

promidat

predictoR:Predictive Data Analysis System

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines and Bayesian Methods.

Maintained by Oldemar Rodriguez. Last updated 1 years ago.

1 stars 2.60 score 3 scripts

cran

BAwiR:Analysis of Basketball Data

Collection of tools to work with European basketball data. Functions available are related to friendly web scraping, data management and visualization. Data were obtained from <https://www.euroleaguebasketball.net/euroleague/>, <https://www.euroleaguebasketball.net/eurocup/> and <https://www.acb.com/>, following the instructions of their respectives robots.txt files, when available. Box score data are available for the three leagues. Play-by-play data are also available for the Spanish league. Methods for analysis include a population pyramid, 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, team shooting plots, team four factors plots, cross-tables with the results of regular season games, maps of nationalities, combinations of lineups, possessions-related variables, timeouts, performance by periods, personal fouls and offensive rebounds. Please see Vinue (2020) <doi:10.1089/big.2018.0124> and Vinue (2024) <doi:10.1089/big.2023.0177>.

Maintained by Guillermo Vinue. Last updated 1 months ago.

1 stars 2.60 score

obreschkow

rglplus:Extension of the 'rgl' 3D Visualization Package

Provides 3D plotting routines that facilitate the use of the 'rgl' package and extend its functionality. For example, the routines allow the user to directly control the camera position & orientation, as well as to generate 3D movies with a moving observer.

Maintained by Danail Obreschkow. Last updated 5 months ago.

2 stars 2.60 score 1 scripts