Construct directed graphs of S4 class hierarchies and visualize them. In general, these graphs typically are DAGs (directed acyclic graphs), often simple trees in practice.

Create an addin in Rstudio to do fill-in-the-middle (FIM) and chat with latest Mistral AI models for coding, Codestral and Codestral Mamba'. For more details about Mistral AI API': <https://docs.mistral.ai/getting-started/quickstart/> and <https://docs.mistral.ai/api/>. For more details about Codestral model: <https://mistral.ai/news/codestral>; about Codestral Mamba': <https://mistral.ai/news/codestral-mamba>.

Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.

Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at the country, region, state, and city levels. The package also downloads world-level COVID-19 data from Johns Hopkins University's repository. COVID-19 data is available from the start of follow-up until to May 5, 2023, when the World Health Organization (WHO) declared an end to the Public Health Emergency of International Concern (PHEIC) for COVID-19.

Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.

Connect to WFP's Moda platform to R, download data, and obtain the list of individuals with access to the project along with their access level.

This package provides a compilation of tests for hypotheses regarding covariance and correlation matrices for one or more groups. The hypothesis can be specified through a corresponding hypothesis matrix and a vector or by choosing one of the basic hypotheses, while for the structure test, only the latter works. Thereby Monte-Carlo and Bootstrap-techniques are used, and the respective method must be chosen, and the functions provide p-values and mostly also estimators of calculated covariance matrices of test statistics. For more details on the methodology, see Sattler et al. (2022) <doi:10.1016/j.jspi.2021.12.001>, Sattler and Pauly (2024) <doi:10.1007/s11749-023-00906-6>, and Sattler and Dobler (2025) <doi:10.48550/arXiv.2310.11799>.

This package implements a basis function or functional data analysis framework for several techniques of multivariate analysis in continuous-time setting. Specifically, we introduced continuous-time analogues of several classical techniques of multivariate analysis, such as principal component analysis, canonical correlation analysis, Fisher linear discriminant analysis, K-means clustering, and so on. Details are in Biplab Paul, Philip T. Reiss, Erjia Cui and Noemi Foa (2025) "Continuous-time multivariate analysis" <doi: 10.1080/10618600.2024.2374570>.

This package provides a generic, easy-to-use and intuitive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on the R packages rxode2 and mrgsolve'. Campsis provides an abstraction layer over the underlying processes of defining a PK/PD model, assembling a custom dataset and running a simulation. The package has a strong dependency on the R package campsismod', which allows models to be read from and written to files, including through a JSON-based interface, and to be adapted further on the fly in the R environment. In addition, campsis allows users to assemble datasets in an intuitive manner, including via a JSON-based interface to import Campsis datasets defined using formal JSON schemas distributed with the package. Once the dataset is ready, the package prepares the simulation, calls rxode2 or mrgsolve (at the user's choice), and returns the results for the given model, dataset and desired simulation settings. The package itself is licensed under the GPL (>= 3); the JSON schema files shipped in inst/extdata are licensed separately under the Creative Commons Attribution 4.0 International (CC BY 4.0).

Assignment of cell type labels to single-cell RNA sequencing (scRNA-seq) clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging when unexpected or poorly described populations are present. The clustermole R package provides methods to query thousands of human and mouse cell identity markers sourced from a variety of databases.

This package provides classes (S4) of circular-linear, symmetric copulas with corresponding methods, extending the copula package. These copulas are especially useful for modeling correlation in discrete-time movement data. Methods for density, (conditional) distribution, random number generation, bivariate dependence measures and fitting parameters using maximum likelihood and other approaches. The package also contains methods for visualizing movement data and copulas.

Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package rkward cannot be installed directly from a repository, as it is a part of RKWard.

Provide a series of functions to conduct a meta analysis of factor analysis based on co-occurrence matrices. The tool can be used to solve the factor structure (i.e. inner structure of a construct, or scale) debate in several disciplines, such as psychology, psychiatry, management, education so on. References: Shafer (2005) <doi:10.1037/1040-3590.17.3.324>; Shafer (2006) <doi:10.1002/jclp.20213>; Loeber and Schmaling (1985) <doi:10.1007/BF00910652>.

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 provides a suite of routines for Clifford algebras, using the Map class of the Standard Template Library. Canonical reference: Hestenes (1987, ISBN 90-277-1673-0, "Clifford algebra to geometric calculus"). Special cases including Lorentz transforms, quaternion multiplication, and Grassmann algebra, are discussed. Vignettes presenting conformal geometric algebra, quaternions and split quaternions, dual numbers, and Lorentz transforms are included. The package follows disordR discipline.

Spatio-temporal data from Scotland used in the vignettes accompanying the CARBayes (spatial modelling) and CARBayesST (spatio-temporal modelling) packages. Most of the data relate to the set of 271 Intermediate Zones (IZ) that make up the 2001 definition of the Greater Glasgow and Clyde health board.

Git hook scripts are useful for identifying simple issues before submission to code review. captain (hook) is an R package to manage and run git pre-commit hooks.

This package provides function declarations and inline function definitions that facilitate communication between R and the Armadillo C++ library for linear algebra and scientific computing. This implementation is detailed in Vargas Sepulveda and Schneider Malamud (2024) <doi:10.1016/j.softx.2025.102087>.

This package provides functions for estimating and reporting multi-year averages and corresponding confidence intervals and distributions. A potential use case is reporting the chemical and ecological status of surface waters according to the European Water Framework Directive.

Provide standard tables, listings, and graphs (TLGs) libraries used in clinical trials. This package implements a structure to reformat the data with dunlin', create reporting tables using rtables and tern with standardized input arguments to enable quick generation of standard outputs. In addition, it also provides comprehensive data checks and script generation functionality.

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.

This package provides tools to visualize the results of a classification or a regression. The graphical displays include stacked plots, silhouette plots, quasi residual plots, class maps, predictions plots, and predictions correlation plots. Implements the techniques described and illustrated in Raymaekers J., Rousseeuw P.J., Hubert M. (2022). Class maps for visualizing classification results. \emphTechnometrics, 64(2), 151â 165. \doi10.1080/00401706.2021.1927849 (open access), Raymaekers J., Rousseeuw P.J.(2022). Silhouettes and quasi residual plots for neural nets and tree-based classifiers. \emphJournal of Computational and Graphical Statistics, 31(4), 1332â 1343. \doi10.1080/10618600.2022.2050249, and Rousseeuw, P.J. (2025). Explainable Linear and Generalized Linear Models by the Predictions Plot. <doi:10.48550/arXiv.2412.16980> (open access). Examples can be found in the vignettes: "Discriminant_analysis_examples","K_nearest_neighbors_examples", "Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples", "Neural_net_examples", and "predsplot_examples".

Cronbach's alpha and various formulas for confidence intervals. The relevant paper is Tsagris M., Frangos C.C. and Frangos C.C. (2013). "Confidence intervals for Cronbach's reliability coefficient". Recent Techniques in Educational Science, 14-16 May, Athens, Greece.

Parallel coordinate plotting with resolutions for large data sets and missing values.