Constructs a shiny app function with interactive displays for conditional visualization of models, data and density functions. An extended version of package condvis'. Catherine B. Hurley, Mark O'Connell,Katarina Domijan (2021) <doi:10.1080/10618600.2021.1983439>.

An interactive application for working with contingency Tables. The application has a template for solving contingency table problems like chisquare test of independence,association plot between two categorical variables. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/CategoricalDataAnalysis/>.

Immune related gene sets provided along with the cinaR package.

Computes the maximum likelihood estimator, the smoothed maximum likelihood estimator and pointwise bootstrap confidence intervals for the distribution function under current status data. Groeneboom and Hendrickx (2017) <doi:10.1214/17-EJS1345>.

The estimation of static and dynamic connectedness measures is created in a modular and user-friendly way. Besides, the time domain connectedness approaches, this package further allows to estimate the frequency connectedness approach, the joint spillover index and the extended joint connectedness approach. In addition, all connectedness frameworks can be based upon orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, the package includes the conditional, decomposed and partial connectedness measures as well as the pairwise connectedness index, influence index and corrected total connectedness index. Finally, a battery of datasets are available allowing to replicate a variety of connectedness papers.

Google's Compact Language Detector 3 is a neural network model for language identification and the successor of cld2 (available from CRAN). The algorithm is still experimental and takes a novel approach to language detection with different properties and outcomes. It can be useful to combine this with the Bayesian classifier results from cld2'. See <https://github.com/google/cld3#readme> for more information.

Clustering method to cluster both effects curves, through quantile regression coefficient modeling, and curves in functional data analysis. Sottile G. and Adelfio G. (2019) <doi:10.1007/s00180-018-0817-8>.

Comprehensive data analysis software, and the name "cg" stands for "compare groups." Its genesis and evolution are driven by common needs to compare administrations, conditions, etc. in medicine research and development. The current version provides comparisons of unpaired samples, i.e. a linear model with one factor of at least two levels. It also provides comparisons of two paired samples. Good data graphs, modern statistical methods, and useful displays of results are emphasized.

Common API for filtering data stored in different data models. Provides multiple filter types and reproducible R code. Works standalone or with shinyCohortBuilder as the GUI for interactive Shiny apps.

This tool performs pairwise correlation analysis and estimate causality. Particularly, it is useful for detecting the metabolites that would be altered by the gut bacteria.

Implementation of estimators for inferring the mean of censored cost data. Including the estimators BT from Bang and Tsiatis (2000) <doi:10.1093/biomet/87.2.329> and ZT from Zhao and Tian (2001) <doi:10.1111/j.0006-341X.2001.01002.x>.

This package 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.

In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The crew.cluster package extends the mirai'-powered crew package with worker launcher plugins for traditional high-performance computing systems. Inspiration also comes from packages mirai by Gao (2023) <https://github.com/r-lib/mirai>, future by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, rrq by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, clustermq by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and batchtools by Lang, Bischl, and Surmann (2017). <doi:10.21105/joss.00135>.

Implementation of Librino, Levorato, and Zorzi (2014) <doi:10.1002/wcm.2305> algorithm for computation of the intersection areas of an arbitrary number of circles.

Classical cryptography methods for words and brief phrases. Substitution, transposition and concealment (null) ciphers are available, like Caesar, Vigenère, Atbash, affine, simple substitution, Playfair, rail fence, Scytale, single column, bifid, trifid, and Polybius ciphers.

This package implements methods for querying data from CalPASS using its API. CalPASS Plus. MMAP API V1. <https://mmap.calpassplus.org/docs/index.html>.

This package provides functions to check whether a vector of p-values respects the assumptions of FDR (false discovery rate) control procedures and to compute adjusted p-values.

This package provides a multi-task learning approach to variable selection regression with highly correlated predictors and sparse effects, based on frequentist statistical inference. It provides statistical evidence to identify which subsets of predictors have non-zero effects on which subsets of response variables, motivated and designed for colocalization analysis across genome-wide association studies (GWAS) and quantitative trait loci (QTL) studies. The ColocBoost model is described in Cao et. al. (2025) <doi:10.1101/2025.04.17.25326042>.

An interface for creating new condition generators objects. Generators are special functions that can be saved in registries and linked to other functions. Utilities for documenting your generators, and new conditions is provided for package development.

This package implements the convex clustering through majorization-minimization (CCMM) algorithm described in Touw, Groenen, and Terada (2022) <doi:10.48550/arXiv.2211.01877> to perform minimization of the convex clustering loss function.

This package provides a chess program which allows the user to create a game, add moves, check for legal moves and game result, plot the board, take back, read and write FEN (Forsythâ Edwards Notation). A basic chess engine based on minimax is implemented.

Flexible framework for coalescent analyses in R. It includes a main function running the MCMC algorithm, auxiliary functions for tree rearrangement, and some functions to compute population genetic parameters. Extended description can be found in Paradis (2020) <doi:10.1201/9780429466700>. For details on the MCMC algorithm, see Kuhner et al. (1995) <doi:10.1093/genetics/140.4.1421> and Drummond et al. (2002) <doi:10.1093/genetics/161.3.1307>.

This package provides functions and a workflow to easily and powerfully calculating specificity, sensitivity and ROC curves of biomarkers combinations. Allows to rank and select multi-markers signatures as well as to find the best performing sub-signatures, now also from single-cell RNA-seq datasets. The method used was first published as a Shiny app and described in Mazzara et al. (2017) <doi:10.1038/srep45477> and further described in Bombaci & Rossi (2019) <doi:10.1007/978-1-4939-9164-8_16>, and widely expanded as a package as presented in the bioRxiv pre print Ferrari et al. <doi:10.1101/2022.01.17.476603>.

This package provides a color mapping is generated according to the break values and corresponding colors. Other colors are generated by interpolating in a certain color space. The functions were part of the circlize package <https://CRAN.R-project.org/package=circlize>.