This package implements a credential chain for Azure OAuth 2.0 authentication based on the package httr2''s OAuth framework. Sequentially attempts authentication methods until one succeeds. During development allows interactive browser-based flows ('Device Code and Auth Code flows) and non-interactive flow ('Client Secret') in batch mode.

This package implements adaptive generalized Bayesian quantile regression with quantile-specific learning rates, HAC-based calibration, Gibbs posterior simulation, posterior summaries, predictive evaluation, and visualization tools. The package builds on the generalized Bayesian composite quantile regression framework of Hardy and Korobilis (2026) <doi:10.2139/ssrn.6618603> by allowing learning rates to vary across quantile levels. The implementation is designed for empirical work with small and moderate time-series samples where posterior calibration and tail-specific inference are important.

Computation of the alpha-shape and alpha-convex hull of a given sample of points in the plane. The concepts of alpha-shape and alpha-convex hull generalize the definition of the convex hull of a finite set of points. The programming is based on the duality between the Voronoi diagram and Delaunay triangulation. The package also includes a function that returns the Delaunay mesh of a given sample of points and its dual Voronoi diagram in one single object.

This package provides access to the Astronomy Engine C library (<https://github.com/cosinekitty/astronomy>) by Don Cross. The library calculates positions of the Sun, Moon, and planets, and predicts astronomical events such as rise/set times, lunar phases, equinoxes, solstices, eclipses, and transits. It is based on the VSOP87 planetary model and is accurate to within approximately one arcminute. This package bundles the single-file C source so that other R packages can link against it via LinkingTo without shipping their own copy.

Construct language-aware lists. Make "and"-separated and "or"-separated lists that automatically conform to the user's language settings.

Adaptive Rejection Sampling, Original version.

This package provides functions to create image annotations through polygon outlining. Annotator has the same function as graphics::locator() but achieves its purpose through drawing, rather than multiple mouse clicks. It is based on the htmlwidgets package and fabric.js JavaScript library <https://fabricjs.com/>.

This package provides algorithms for creating artworks in the ggplot2 language that incorporate some form of randomness.

This package contains data from an observational study concerning possible effects of light daily alcohol consumption on survival and on HDL cholesterol. It also replicates various simple analyses in Rosenbaum (2025) <doi:10.1080/09332480.2025.2473291>. Finally, it includes new R code in wgtRankCef() that implements and replicates a new method for constructing evidence factors in observational block designs in Rosenbaum (2026) <doi:10.1080/01621459.2026.2624858>).

Adaptive and Robust Transfer Learning (ART) is a flexible framework for transfer learning that integrates information from auxiliary data sources to improve model performance on primary tasks. It is designed to be robust against negative transfer by including the non-transfer model in the candidate pool, ensuring stable performance even when auxiliary datasets are less informative. See the paper, Wang, Wu, and Ye (2023) <doi:10.1002/sta4.582>.

Simulation and estimation tools for various types of ambit processes, including trawl processes and weighted trawl processes.

The functions proposed in this package allows to evaluate the process of measurement of the chemical components of water numerically or graphically. TSSS(), ICHS and datacheck() functions are useful to control the quality of measurements of chemical components of a sample of water. If one or more measurements include an error, the generated graph will indicate it with a position of the point that represents the sample outside the confidence interval. The function CI() allows to evaluate the possibility of contamination of a water sample after being obtained. Validation() is a function that allows to calculate the quality parameters of a technique for the measurement of a chemical component.

An interactive document on the topic of one-way and two-way analysis of variance using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://kartikeyab.shinyapps.io/ANOVAShiny/>.

This package provides a chat package connecting to API endpoints by OpenAI (<https://platform.openai.com/>) to answer questions (about R).

This package provides algorithms for frequency-based pairing of alpha-beta T cell receptors.

Create beautiful and interactive visualizations in a single function call. The data.table package is utilized to perform the data wrangling necessary to prepare your data for the plot types you wish to build, along with allowing fast processing for big data. There are two broad classes of plots available: standard plots and machine learning evaluation plots. There are lots of parameters available in each plot type function for customizing the plots (such as faceting) and data wrangling (such as variable transformations and aggregation).

This package provides a client for AWS Translate <https://aws.amazon.com/documentation/translate>, a machine translation service that will convert a text input in one language into a text output in another language.

This package provides several methods for aggregating probabilistic forecasts. You have a group of people who have made probabilistic forecasts for the same event. You want to take advantage of the "wisdom of the crowd" and combine these forecasts in some sensible way. This package provides implementations of several strategies, including geometric mean of odds, an extremized aggregate (Neyman, Roughgarden (2021) <doi:10.1145/3490486.3538243>), and "high-density trimmed mean" (Powell et al. (2022) <doi:10.1037/dec0000191>).

Static code compilation of a shiny app given an R function (into ui.R and server.R files or into a shiny app object). See examples at <https://github.com/alekrutkowski/autoshiny>.

This package provides tools and functions to efficiently create datasets used in pharmacometric analysis. Additional functionality is added to create documentation and prepare files for submission and quality control purposes.

Checks function arguments, ideally for use in R packages. Uses a simple interface and produces clean, informative error messages using cli'.

This package implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.

This package implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees as described in Vega Yon et al. (2021) <doi:10.1371/journal.pcbi.1007948>. Focusing on computational efficiency, aphylo makes it possible to estimate pooled phylogenetic models, including thousands (hundreds) of annotations (trees) in the same run. The package also provides the tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction) and goodness-of-fit assessment featured in Vega Yon et al. (2021).

This package provides methods to analyse the stability of non-deterministic prediction models. Prediction stability is quantified either as data-based prediction stability (phi) or as model-based prediction stability (psi). The package implements measures for categorical, ordinal, and metric predictions based on repeated model fitting and corresponding predictions. Methods are based on Lange et al. (2025) <doi:10.1186/s12859-025-06097-1>.