The biglm package lets you create a linear model object that uses only codep^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory.

This package is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted.

This package provides a collection of Lua filters that extend the functionality of R Markdown templates (e.g., count words or post-process citations).

This package provides a framework to create Bootstrap 3 HTML reports from knitr Rmarkdown.

This package provides an implementation of interpreted string literals, inspired by Python's Literal String Interpolation (PEP-0498) and Docstrings (PEP-0257) and Julia's Triple-Quoted String Literals.

This package provides tools for circular statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.

This package is a port of the new http://matplotlib.org/ color maps (viridis--the default--, magma, plasma, and inferno) to R. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. They are also designed to be perceived by readers with the most common form of color blindness.

This package contains various tools for working with and evaluating cross-validated area under the ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals for cross-validated AUC estimates based on influence curves for i.i.d. and pooled repeated measures data, respectively.

This package provides functions for fitting and plotting SITAR growth curve models. SITAR is a shape- invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales.

This package provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations).

This package provides header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <https://en.wikipedia.org/wiki/Hungarian_algorithm>; Kuhn (1955) <doi:10.1002/nav.3800020109>).

The R6 package allows the creation of classes with reference semantics, similar to R's built-in reference classes. Compared to reference classes, R6 classes are simpler and lighter-weight, and they are not built on S4 classes so they do not require the methods package. These classes allow public and private members, and they support inheritance, even when the classes are defined in different packages.

This package provides functions to calculate: moments, Pearson's kurtosis, Geary's kurtosis and skewness; it also includes tests related to them (Anscombe-Glynn, D'Agostino, Bonett-Seier).

This package provides a utility for R to parse a bibtex file.

This package provides tools for exploratory data analysis and data visualization of biological sequence (DNA and protein) data. It also includes utilities for sequence data management under the ACNUC system.

This package provides functions for the quality control, homogenization and missing data infilling of climatological series, and to obtain climatological summaries and grids from the results. Also functions to draw wind-roses and Walter&Lieth climate diagrams are included.

This package provides a general toolkit for downloading, managing, analyzing, and presenting data from the U.S. Census, including SF1 (Decennial short-form), SF3 (Decennial long-form), and the American Community Survey (ACS). Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. The package provides new methods to conduct standard operations on acs objects and present/plot data in statistically appropriate ways.

This package provides the tools necessary to do non-standard evaluation (NSE) in R.

This R package caches the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

This package provides a collection of functions to create spatial weights matrix objects from polygon contiguities, from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree.

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

This package provides useful functions to deal with the haven_labelled and haven_labelled_spss classes introduced by the haven package.

This package provides a minimal R client to access the GitHub API.

This package provides functionality to compute various node centrality measures on networks. Included are functions to compute betweenness centrality (by utilizing Madduri and Bader's SNAP library), implementations of Burt's constraint and effective network size (ENS) metrics, Borgatti's algorithm to identify key players, and Valente's bridging metric. The betweenness, Key Players, and bridging implementations are parallelized with OpenMP.