This package implements Dirichlet regression models.

This package provides functions for importing and handling text files and formatted text files with additional meta-data, such including .csv, .tab, .json, .xml, .html, .pdf, .doc, .docx, .rtf, .xls, .xlsx, and others.

This package provides a wrapper for the Intro.js library. This package makes it easy to include step-by-step introductions, and clickable hints in a Shiny application. It supports both static introductions in the UI, and programmatic introductions from the server-side.

This package provides a language extension to efficiently write functional programs in R. Syntax extensions include multi-part function definitions, pattern matching, guard statements, built-in (optional) type safety.

Least Angle Regression ("LAR") is a model selection algorithm; a useful and less greedy version of traditional forward selection methods. A simple modification of the LAR algorithm implements Tibshirani's Lasso; the Lasso modification of LARS calculates the entire Lasso path of coefficients for a given problem at the cost of a single least squares fit. Another LARS modification efficiently implements epsilon Forward Stagewise linear regression.

This package provides data used as examples to demonstrate GAMLSS models.

The fit.models function and its associated methods (coefficients, print, summary, plot, etc.) were originally provided in the robust package to compare robustly and classically fitted model objects. The aim of the fit.models package is to separate this fitted model object comparison functionality from the robust package and to extend it to support fitting methods (e.g., classical, robust, Bayesian, regularized, etc.) more generally.

This package performs angle-based outlier detection on a given data frame. It offers three methods to process data:

1. full but slow implementation using all the data that has cubic complexity;

2. a fully randomized method;

3. a method using k-nearest neighbours.

These algorithms are well suited for high dimensional data outlier detection.

This package is a data visualization package for R providing an implementation of an interactive grammar of graphics, taking the best parts of ggplot2, combining them with the reactive framework of Shiny and drawing web graphics using Vega.

This package provides statistical models of biased sampling in the form of univariate and multivariate noncentral hypergeometric distributions, including Wallenius' noncentral hypergeometric distribution and Fisher's noncentral hypergeometric distribution (also called extended hypergeometric distribution).

This package lets you compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

Deciding what resolution to use can be a difficult question when approaching a clustering analysis. One way to approach this problem is to look at how samples move as the number of clusters increases. This package allows you to produce clustering trees, a visualization for interrogating clusterings as resolution increases.

This package provides a collection of templates to author preregistration documents for scientific studies in PDF format.

This package provides iterative methods for matrix completion that use nuclear-norm regularization. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank single value decompositions (SVDs) on large sparse centered matrices (i.e. principal components).

This package lets you read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are natively supported by browsers via the JavaScript WebCryptoAPI, and used by services like OAuth 2.0, LetsEncrypt, and Github Apps.

This package provides code analysis tools for R to check R code for possible problems.

This package completes R's functional programming tools with missing features present in other programming languages.

This package implements various estimators of entropy, such as the shrinkage estimator by Hausser and Strimmer, the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, and the Chao-Shen estimator. It also offers an R interface to the NSB estimator. Furthermore, it provides functions for estimating Kullback-Leibler divergence, chi-squared, mutual information, and chi-squared statistic of independence. In addition there are functions for discretizing continuous random variables.

This is a package for reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in R, using GDAL bindings provided by sf, and NetCDF bindings by ncmeta and RNetCDF.

This package provides procedures for fitting a principal curve to a data matrix in arbitrary dimensions.

This package helps you create plots of p-values using single SNP and/or haplotype data. Main features of the package include options to display a linkage disequilibrium (LD) plot and the ability to plot multiple datasets simultaneously. Plots can be created using global and/or individual haplotype p-values along with single SNP p-values. Images are created as either PDF/EPS files.

This package provides an R Client for the Europe PubMed Central RESTful Web Service. It gives access to both metadata on life science literature and open access full texts. Europe PMC indexes all PubMed content and other literature sources including Agricola, a bibliographic database of citations to the agricultural literature, or Biological Patents. In addition to bibliographic metadata, the client allows users to fetch citations and reference lists. Links between life-science literature and other EBI databases, including ENA, PDB or ChEMBL are also accessible.

The sqldf function is typically passed a single argument which is an SQL select statement where the table names are ordinary R data frame names. sqldf transparently sets up a database, imports the data frames into that database, performs the SQL statement and returns the result using a heuristic to determine which class to assign to each column of the returned data frame. The sqldf or read.csv.sql functions can also be used to read filtered files into R even if the original files are larger than R itself can handle.

This package provides functions for numerical analysis and linear algebra, numerical optimization, differential equations, plus some special functions. It uses Matlab function names where appropriate to simplify porting.