Download and parse public files released by B3 and convert them into useful formats and data structures common to data analysis practitioners.

Model relational and durational events in a counting process framework, with functions for estimating and simulating Relational Event Models (REM) and Durational Event Models (DEM). Includes support for time-varying covariates, windowed statistics, and high-dimensional node-level fixed effects. References include Fritz et al. (2026) "Scalable Durational Event Models: Application to Physical and Digital Interactions" <doi:10.48550/arXiv.2504.00049>.

Automatic open data acquisition from resources of Polish Head Office of Geodesy and Cartography ('GŠówny UrzÄ d Geodezji i Kartografii') (<https://www.gov.pl/web/gugik>). Available datasets include various types of numeric, raster and vector data, such as orthophotomaps, digital elevation models (digital terrain models, digital surface model, point clouds), state register of borders, spatial databases, geometries of cadastral parcels, 3D models of buildings, and more. It is also possible to geocode addresses or objects using the geocodePL_get() function.

This package provides a simple set of wrappers to easily use RDCOMClient for generating Microsoft PowerPoint presentations. Warning:this package is soon to be archived from CRAN.

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).

Evaluates R source codes by variable and/or functions names. Similar source codes should deliver similarity coefficients near one. Since neither the frequency nor the order of the used names is considered, a manual inspection of the R source code is required to check for similarity. Possible use cases include detection of code clones for improving software quality and of plagiarism amongst students assignments.

Relational Class Analysis (RCA) is a method for detecting heterogeneity in attitudinal data (as described in Goldberg A., 2011, Am. J. Soc, 116(5)).

Downloads and parses SDF (Structural Description Format) and PDB (Protein Database) files for 3D rendering.

An approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information on accumulation rates and their variability. See Blaauw & Christen (2011).

Qualify R software installations using R Markdown as the foundation for the Installation Qualification (IQ) and Operational Qualification (OQ) when used in environments (such as regulated clinical trials) where such processes may be required.

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.

This package produces Shiny applications for different types of popular functional data analyses. The functional data analyses are implemented in the refund package, then refund.shiny reads in the refund object and implements an object-specific set of plots based on the object class using S3.

Functionality for performing a principled reference analysis in the Bayesian normal-normal hierarchical model used for Bayesian meta-analysis, as described in Ott, Plummer and Roos (2021) <doi:10.1002/sim.9076>. Computes a reference posterior, induced by a minimally informative improper reference prior for the between-study (heterogeneity) standard deviation. Determines additional proper anti-conservative (and conservative) prior benchmarks. Includes functions for reference analyses at both the posterior and the prior level, which, given the data, quantify the informativeness of a heterogeneity prior of interest relative to the minimally informative reference prior and the proper prior benchmarks. The functions operate on data sets which are compatible with the bayesmeta package.

This reduced piecewise exponential survival software implements the likelihood ratio test and backward elimination procedure in Han, Schell, and Kim (2012 <doi:10.1080/19466315.2012.698945>, 2014 <doi:10.1002/sim.5915>), and Han et al. (2016 <doi:10.1111/biom.12590>). Inputs to the program can be either times when events/censoring occur or the vectors of total time on test and the number of events. Outputs of the programs are times and the corresponding p-values in the backward elimination. Details about the model and implementation are given in Han et al. 2014. This program can run in R version 3.2.2 and above.

The aim of the report package is to bridge the gap between Râ s output and the formatted results contained in your manuscript. This package converts statistical models and data frames into textual reports suited for publication, ensuring standardization and quality in results reporting.

Access Synthesize Bio models from their API <https://app.synthesize.bio/> using this wrapper that provides a convenient interface to the Synthesize Bio API, allowing users to generate realistic gene expression data based on specified biological conditions. This package enables researchers to easily access AI-generated transcriptomic data for various modalities including bulk RNA-seq, single-cell RNA-seq, microarray data, and more.

Data sets for Chihara and Hesterberg (2022, ISBN: 978-1-119-87404-1) "Mathematical Statistics with Resampling in R" (3rd Ed).

Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises parametric families.

IUCN Red List (<https://api.iucnredlist.org/>) client. The IUCN Red List is a global list of threatened and endangered species. Functions cover all of the Red List API routes. An API key is required.

This package implements two-sample tests for paired data with missing values (Fong, Huang, Lemos and McElrath 2018, Biostatics, <doi:10.1093/biostatistics/kxx039>) and modified Wilcoxon-Mann-Whitney two sample location test, also known as the Fligner-Policello test.

Interface for the Google Ads API'. Google Ads is an online advertising service that enables advertisers to display advertising to web users (see <https://developers.google.com/google-ads/> for more information).

This package provides an interface to Mapzen'-based APIs (including geocode.earth, Nextzen, and NYC GeoSearch) for geographic search and geocoding, isochrone calculation, and vector data to draw map tiles. See <https://www.mapzen.com/documentation/> for more information. The original Mapzen has gone out of business, but rmapzen can be set up to work with any provider who implements the Mapzen API.

This package provides a unified workflow for relational event modeling by re-exporting core functions from remify', remstats', and remstimate'. Supports tie-oriented and actor-oriented modeling with frequentist and Bayesian estimation. Methods are described in Butts (2008) <doi:10.1111/j.1467-9531.2008.00203.x> and Stadtfeld and Block (2017) <doi:10.1177/0081175017709295>.

Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval Method is designed to perform multi-criteria decision-making (MCDM), developed by Mališa Žižovic in 2020 (<doi:10.3390/math8061015>). It calculates the final sorted rankings based on a decision matrix where rows represent alternatives and columns represent criteria. The method uses: - A numeric vector of weights for each criterion (the sum of weights must be 1). - A numeric vector of ideal values for each criterion. - A numeric vector of anti-ideal values for each criterion. - Numeric values representing the extent to which the ideal value is preferred over the anti-ideal value, and the extent to which the anti-ideal value is considered worse. The function standardizes the decision matrix, normalizes the data, applies weights, and returns the final sorted rankings.