This package provides tools for creating data validation pipelines and tidy reports. This package offers a framework for exploring and validating data frame like objects using dplyr grammar of data manipulation.

This package provides realistic synthetic example datasets for the R4SUB (R for Regulatory Submission) ecosystem. Includes a pharma study evidence table, ADaM (Analysis Data Model) and SDTM (Study Data Tabulation Model) metadata following CDISC (Clinical Data Interchange Standards Consortium) conventions (<https://www.cdisc.org>), traceability mappings, a risk register based on ICH (International Council for Harmonisation) Q9 quality risk management principles (<https://www.ich.org/page/quality-guidelines>), and regulatory indicator definitions. Designed for demos, vignettes, and package testing.

This package provides a flexible alternative to the built-in rank() function called smartrank(). Optionally rank categorical variables by frequency (instead of in alphabetical order), and control whether ranking is based on descending/ascending order. smartrank() is suitable for both numerical and categorical data.

Connect, query, and operate on information available from the Open Source Vulnerability database <https://osv.dev/>. Although CRAN has vulnerabilities listed, these are few compared to projects such as PyPI'. With tighter integration between R and Python', having an R specific package to access details about vulnerabilities from various sources is a worthwhile enterprise.

This package provides data structures and functions for file input/output in the ribios software suite, supporting common bioinformatics and computational biology file formats, designed for fast loading and high performance with minimal dependencies.

Imports data from the SurveyXact commercial service <https://rambollxact.com>, adds variable labels, and converts value labels to factors in the same order as exported from SurveyXact'.

This package provides teaching datasets and helper functions to support the open educational resource Martinez (2026) "Reproducible Research Using R" <doi:10.5281/zenodo.19136755>. The package includes datasets used throughout the book and utilities to list and copy chapter scripts shipped with the package.

Reproducible, programmatic retrieval of datasets from the Roper Center data archive. The Roper Center for Public Opinion Research <https://ropercenter.cornell.edu> maintains the largest archive of public opinion data in existence, but researchers using these datasets are caught in a bind. The Center's terms and conditions bar redistribution of downloaded datasets, but to ensure that one's work can be reproduced, assessed, and built upon by others, one must provide access to the raw data one employed. The `ropercenter` package cuts this knot by providing registered users with programmatic, reproducible access to Roper Center datasets from within R.

Randomization lists are an integral component of randomized clinical trials. randotools provides tools to easily create such lists.

This package creates interactive graphs with R'. It joins the data analysis power of R and the visualization libraries of JavaScript in one package.

This package provides tools to download, process, and analyze real-time meteorological radar images from Simepar (Paraná, Brazil) <https://www.simepar.br/simepar/radar_msc>. Designed to support the Rede Agropesquisa hydrological monitoring, it includes functions to detect rainfall intensity based on Red, Green, and Blue (RGB) color values within predefined circular study areas. Features automated integration with the Telegram Bot API <https://core.telegram.org/bots/api> to send spatialized image alerts and an interactive shiny dashboard for easy configuration and continuous weather tracking.

Calculates intra-regional and inter-regional similarities based on user-provided spatial vector objects (regions) and spatial raster objects (cells with values). Implemented metrics include inhomogeneity, isolation (Haralick and Shapiro (1985) <doi:10.1016/S0734-189X(85)90153-7>, Jasiewicz et al. (2018) <doi:10.1016/j.cageo.2018.06.003>), and distinction (Nowosad (2021) <doi:10.1080/13658816.2021.1893324>).

Empirical orthogonal teleconnections in R. remote is short for R(-based) EMpirical Orthogonal TEleconnections'. It implements a collection of functions to facilitate empirical orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections (EOTs) denote a regression based approach to decompose spatio-temporal fields into a set of independent orthogonal patterns. They are quite similar to Empirical Orthogonal Functions (EOFs) with EOTs producing less abstract results. In contrast to EOFs, which are orthogonal in both space and time, EOT analysis produces patterns that are orthogonal in either space or time.

This package provides randomization tests and graphical diagnostics for assessing randomized assignment and covariate balance for a binary treatment variable. See Branson (2021) <arXiv:1804.08760> for details.

Restricted Cubic Splines were performed to explore the shape of association form of "U, inverted U, L" shape and test linearity or non-linearity base on "Cox,Logistic,linear,quasipoisson" regression, and auto output Restricted Cubic Splines figures. rcssci package could automatically draw RCS graphics with Y-axis "OR,HR,RR,beta". The Restricted Cubic Splines method were based on Suli Huang (2022) <doi:10.1016/j.ecoenv.2022.113183>,Amit Kaura (2019) <doi:10.1136/bmj.l6055>, and Harrell Jr (2015, ISBN:978-3-319-19424-0 (Print) 978-3-319-19425-7 (Online)).

This package provides efficient functions for detecting multiple change points in multidimensional time series. The models can be piecewise constant or polynomial. Adaptive threshold selection methods are available, see Fan and Wu (2024) <arXiv:2403.00600>.

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.

This package provides a full-featured RethinkDB <https://rethinkdb.com/> client for R; allows users to store JSON-serialised data in a robust, distributed no-SQL system, use rich queries and react to data changes in real-time.

Encapsulates functions to streamline calls from R to the REDCap API. REDCap (Research Electronic Data CAPture) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The Application Programming Interface (API) offers an avenue to access and modify data programmatically, improving the capacity for literate and reproducible programming.

Permite obtener rápidamente una serie de medidas de resumen y gráficos para datos numéricos discretos o continuos en series simples. También permite obtener tablas de frecuencia clásicas y gráficos cuando se desea realizar un análisis de series agrupadas. Su objetivo es de aplicación didáctica para un curso introductorio de Bioestadà stica utilizando el software R, para las carreras de grado las carreras de grado y otras ofertas educativas de la Facultad de Ciencias Agrarias de la UNJu / It generates summary measures and graphs for discrete or continuous numerical data in simple series. It also enables the creation of classic frequency tables and graphs when analyzing grouped series. Its purpose is for educational application in an introductory Biostatistics course using the R software, aimed at undergraduate programs and other educational offerings of the Faculty of Agricultural Sciences at the National University of Jujuy (UNJu).

Rcmdr menu support for many of the functions in the HH package. The focus is on menu items for functions we use in our introductory courses.

This package implements the rank-ordered logit (RO-logit) model for stratified analysis of continuous outcomes introduced by Tan et al. (2017) <doi:10.1177/0962280217747309>. Model diagnostics based on the heuristic residuals and estimates in linear scales are available from the package, and outcomes with ties are supported.

Get the category of content hosted by a domain. Use Shallalist (service discontinued), VirusTotal (which provides access to lots of services) <https://www.virustotal.com/>, DMOZ <https://archive.org/details/dmoz-rdf-20150327>, University Domain list <https://github.com/Hipo/university-domains-list>, OpenAI GPT models, Anthropic Claude models, or validated machine learning classifiers based on Shallalist data to learn about the kind of content hosted by a domain.

An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Hoffman *et al.* (1999) (<doi:10.1145/331770.331775>) for original implementation, see Di Caro *et al* (2012) (<doi:10.1007/978-3-642-13672-6_13>), for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.