Set of functions to quantify and map the behaviour of winds generated by tropical storms and cyclones in space and time. It includes functions to compute and analyze fields such as the maximum sustained wind field, power dissipation index and duration of exposure to winds above a given threshold. It also includes functions to map the trajectories as well as characteristics of the storms.

This package provides a declarative interface for statistical inference built on the S7 object system. The layouts of the statistical inference are described using expressive variable mappers, null hypotheses are stated as mathematical expressions over population parameters, and estimation is deferred until explicitly requested. Supports estimation method involving hypothesis testing and model-based inference with an extensible variant system for registering custom estimation methods.

This package provides a utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

This package implements the bootstrap slope heterogeneity test for panel data based on Blomquist and Westerlund (2015) <doi:10.1007/s00181-015-0978-z>. Tests the null hypothesis that slope coefficients are homogeneous across cross-sectional units. Provides both standard and adjusted Delta statistics with bootstrap p-values. Supports partialling out of control variables and cross-sectional averages for dealing with cross-sectional dependence.

This package lets you carry out network-based gene set analysis by incorporating external information about interactions among genes, as well as novel interactions learned from data. It implements methods described in Shojaie A, Michailidis G (2010) <doi:10.1093/biomet/asq038>, Shojaie A, Michailidis G (2009) <doi:10.1089/cmb.2008.0081>, and Ma J, Shojaie A, Michailidis G (2016) <doi:10.1093/bioinformatics/btw410>.

The encoding of color can be handled in many different ways, using different color spaces. As different color spaces have different uses, efficient conversion between these representations are important. This package provides a set of functions that gives access to very fast color space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the convertColor function in the grDevices package.

Radicale is a CalDAV and CardDAV server for UNIX-like platforms. Calendars and address books are available for both local and remote access, possibly limited through authentication policies. They can be viewed and edited by calendar and contact clients on mobile phones or computers.

Radicale intentionally does not fully comply with the CalDAV and CardDAV RFCs. Instead, it supports the CalDAV and CardDAV implementations of popular clients.

Reprepro is a tool to manage a repository of Debian packages (.deb, .udeb, .dsc, ...). It stores files either being injected manually or downloaded from some other repository (partially) mirrored into one pool/ hierarchy. Managed packages and files are stored in a Berkeley DB, so no database server is needed. Checking signatures of mirrored repositories and creating signatures of the generated Package indices is supported.

The xvfb-run wrapper simplifies running commands and scripts within a virtual X server environment. It sets up an X authority file or uses an existing user-specified one, writes a cookie to it, and then starts the Xvfb X server as a background process. It also takes care of killing the server and cleaning up before returning the exit status of the command.

comapr detects crossover intervals for single gametes from their haplotype states sequences and stores the crossovers in GRanges object. The genetic distances can then be calculated via the mapping functions using estimated crossover rates for maker intervals. Visualisation functions for plotting interval-based genetic map or cumulative genetic distances are implemented, which help reveal the variation of crossovers landscapes across the genome and across individuals.

Epidemiological population dynamics models traditionally define a pathogen's virulence as the increase in the per capita rate of mortality of infected hosts due to infection. This package provides functions allowing virulence to be estimated by maximum likelihood techniques. The approach is based on the analysis of relative survival comparing survival in matching cohorts of infected vs. uninfected hosts (Agnew 2019) <doi:10.1101/530709>.

The functions in this package inspect, read, edit and run files for APSIM "Next Generation" ('JSON') and APSIM "Classic" ('XML'). The files with an apsim extension correspond to APSIM Classic (7.x) - Windows only - and the ones with an apsimx extension correspond to APSIM "Next Generation". For more information about APSIM see (<https://www.apsim.info/>) and for APSIM next generation (<https://apsimnextgeneration.netlify.app/>).

To address the violation of the assumption of normally distributed variables, researchers frequently employ bootstrapping. Building upon established packages for R (Sigmann et al. (2024) <doi:10.32614/CRAN.package.afex>, Lenth (2024) <doi:10.32614/CRAN.package.emmeans>), we provide bootstrapping functions to approximate a normal distribution of the parameter estimates for between-subject, within-subject, and mixed one-way and two-way ANOVA.

Semi-relaxed inverse optimal transport (IOT) for single-cell state-transition and pseudotime analysis: a self-contained R solver (Anderson-accelerated soft Sinkhorn with exact implicit gradients), feature-weight fitting with a two-stage bias-corrected refit and multi-restart, state transition matrices, random-walk pseudotime, ggplot2 visualisation, soft-gated Seurat and SingleCellExperiment interfaces, reproducible simulated demo data, and bulk-cohort pathway scoring utilities.

An implementation of intervention effect estimation for DAGs (directed acyclic graphs) learned from binary or continuous data. First, parameters are estimated or sampled for the DAG and then interventions on each node (variable) are propagated through the network (do-calculus). Both exact computation (for continuous data or for binary data up to around 20 variables) and Monte Carlo schemes (for larger binary networks) are implemented.

Income tax calculations for England, Northern Ireland and Wales. Estimate annual income tax within the different taxation bands at specified levels of both taxable income and the Personal Allowance, emulating the results obtained at <https://www.gov.uk/estimate-income-tax>. Calculate the standard Personal Allowance at various levels of taxable income. Estimate the personal allowance required to recoup a specified amount of income tax.

Fits unimodal and multimodal gambin distributions to species-abundance distributions from ecological data, as in in Matthews et al. (2014) <DOI:10.1111/ecog.00861>. gambin is short for gamma-binomial'. The main function is fit_abundances(), which estimates the alpha parameter(s) of the gambin distribution using maximum likelihood. Functions are also provided to generate the gambin distribution and for calculating likelihood statistics.

The method aims to identify important factors in screening experiments by aggregation over random models as studied in Singh and Stufken (2022) <doi:10.48550/arXiv.2205.13497>. This package provides functions to run the Gauss-Dantzig selector on screening experiments when interactions may be affecting the response. Currently, all functions require each factor to be at two levels coded as +1 and -1.

Computes G-Wishart normalising constants through a Fourier approach. Either exact analytical results, numerical integration or Monte Carlo estimation are employed. Details at C. Wong, G. Moffa and J. Kuipers (2024), <doi:10.48550/arXiv.2404.06803>. Also includes approximations of the ratio of normalising constants, see details at C. Wong, G. Moffa and J. Kuipers (2025), <doi:10.48550/arXiv.2503.13046>.

An implementation of the modelling and reporting features described in reference textbook and guidelines (Briggs, Andrew, et al. Decision Modelling for Health Economic Evaluation. Oxford Univ. Press, 2011; Siebert, U. et al. State-Transition Modeling. Medical Decision Making 32, 690-700 (2012).): deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc.

An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website <https://www.ipums.org>.

Vector operations between grapes: An infix-only package! The invctr functions perform common and less common operations on vectors, data frames matrices and list objects: - Extracting a value (range), or, finding the indices of a value (range). - Trimming, or padding a vector with a value of your choice. - Simple polynomial regression. - Set and membership operations. - General check & replace function for NAs, Inf and other values.

Interact with the Entrez API hosted by the National Center for Biotechnology Information (NCBI), <https://www.ncbi.nlm.nih.gov/books/NBK25499/>. This package is focused on working with sequence metadata and links. It handles pagination and compensates for some API limitations to simplify these tasks. API calls are printed to the console to highlight how high-level queries are translated into individual HTTP requests.

This package implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. For optional comparisons, install remMap from GitHub (<https://github.com/cran/remMap>).