Defines functions that can be used to collect provenance as an R script executes or during a console session. The output is a text file in PROV-JSON format.

Enhances the R Optimization Infrastructure ('ROI') package with the quadratic solver OSQP'. More information about OSQP can be found at <https://osqp.org>.

Tskit enables efficient storage, manipulation, and analysis of ancestral recombination graphs (ARGs) using succinct tree sequence encoding. The tree sequence encoding of an ARG is described in Wong et al. (2024) <doi:10.1093/genetics/iyae100>, while `tskit` project is described in Jeffrey et al. (2026) <doi:10.48550/arXiv.2602.09649>. See also <https://tskit.dev> for project news, documentation, and tutorials. Tskit provides Python', C', and Rust application programming interfaces (APIs). The Python API can be called from R via the reticulate package to load and analyse tree sequences as described at <https://tskit.dev/tutorials/tskitr.html>. RcppTskit provides R access to the tskit C API for cases where the reticulate option is not optimal; for example, high-performance or low-level work with tree sequences. Currently, RcppTskit provides a limited set of R functions because the Python API and reticulate already covers most needs.

This package provides methods for calculation and visualization of the Repertoire Dissimilarity Index. Citation: Bolen and Rubelt, et al (2017) <doi:10.1186/s12859-017-1556-5>.

The rkafkajars package collects all the external jars required for the rkafka package.

Perform the complete processing of a set of proton nuclear magnetic resonance spectra from the free induction decay (raw data) and based on a processing sequence (macro-command file). An additional file specifies all the spectra to be considered by associating their sample code as well as the levels of experimental factors to which they belong. More detail can be found in Jacob et al. (2017) <doi:10.1007/s11306-017-1178-y>.

This package provides a collection of palettes designed to integrate with ggplot', reflecting the color schemes associated with ConesaLab'.

Loading calls data from Ringostat API'. See <https://help.ringostat.com/knowledge-base/article/integration-with-ringostat-via-api>.

This package provides functions to compute the modularity and modularity-related roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, 2005, <doi:10.1038/nature03288>).

This package provides functions to have nice rmarkdown outputs of the seasonal and trading day adjustment models made with RJDemetra'.

Computes linear Bayesian spectral estimates from multirate data for second-order stationary time series. Provides credible intervals and methods for plotting various spectral estimates. Please see the paper `Should we sample a time series more frequently? (doi below) for a full description of and motivation for the methodology.

Use the <https://api.nbp.pl/> API through R. Retrieve currency exchange rates and gold prices data published by the National Bank of Poland in form of convenient R objects.

Reversion mutations are secondary mutations that reverse the deleterious effects of an original pathogenic mutation, partially or fully restoring the gene's function. The revert package detects reversion mutations for a specific pathogenic mutation from DNA-seq bam files.

Use JSON templates to create folders and files structure for data science projects. Includes customized templates and accepts your own as JSON files.

Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into extensible time series format, and support for writing Raven input files. The RavenR package is also archived at Chlumsky et al. (2020) <doi:10.5281/zenodo.4248183>. The Raven Hydrologic Modelling Framework method can be referenced with Craig et al. (2020) <doi:10.1016/j.envsoft.2020.104728>.

Function for generating random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.

Plots the Receiver Operating Characteristics Surface for high-throughput class-skewed data, calculates the Volume under the Surface (VUS) and the FDR-Controlled Area Under the Curve (FCAUC), and conducts tests to compare two ROC surfaces. Computes eROC curve and the corresponding AUC for imperfect reference standard.

An implementation of functionalities to transform directed graphs that are bound to a set of known forbidden paths. There are several transformations, following the rules provided by Villeneuve and Desaulniers (2005) <doi: 10.1016/j.ejor.2004.01.032>, and Hsu et al. (2009) <doi: 10.1007/978-3-642-03095-6_60>. The resulting graph is generated in a data-frame format. See rsppfp website for more information, documentation an examples.

This package provides helper functions for authenticating and retrieving data from your ODK-X Sync Endpoint'. This is an early release intended for testing and feedback.

Provide estimation and data generation tools for the quantile generalized beta regression model. For details, see Bourguignon, Gallardo and Saulo <arXiv:2110.04428> The package also provides tools to perform covariates selection.

FRACTRAN is an obscure yet tantalizing programming language invented by John Conway of Game of Life fame. The code consists of a sequence of fractions. The rules are simple. First, select an integer to initialize the process. Second, multiply the integer by the first fraction. If an integer results, start again with the new integer. If not, try the next fraction. Finally, if no such multiplication yields an integer, terminate the program. For more information, see <https://en.wikipedia.org/wiki/FRACTRAN> .

Clinical care data from 130 U.S. hospitals in the years 1999-2008 adapted from the study Strack et al. (2014) <doi:10.1155/2014/781670>. Each row describes an "encounter" with a patient with diabetes, including variables on demographics, medications, patient history, diagnostics, payment, and readmission.

Lightweight helpers for checking whether empirical results remain substantively unchanged across code revisions, platform differences, and package updates. The package supports regression-style testing of derived datasets, statistical model outputs, tables, and plots, helping researchers detect unintended result drift early and distinguish material from non-material changes in empirical workflows.

An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data as presented in Sarrias (2016) <doi:10.18637/jss.v074.i10>.