This package provides functions to read flat or tabular text files from disk (or a connection).

Constructs confidence intervals on the probability of success in a binomial experiment via several parameterizations

This package lets you edit and simplify geojson, Spatial, and sf objects. This is a wrapper around the mapshaper JavaScript library to perform topologically-aware polygon simplification, as well as other operations such as clipping, erasing, dissolving, and converting multi-part to single-part geometries.

This package provides mosaic plots for the ggplot2 framework. Mosaic plot functionality is provided in a single ggplot2 layer by calling the geom mosaic.

This package makes the qhull library available in R, in a similar manner as in Octave. Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2-d, 3-d, 4-d, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull does not support constrained Delaunay triangulations, or mesh generation of non-convex objects, but the package does include some R functions that allow for this. Currently the package only gives access to Delaunay triangulation and convex hull computation.

This package provides functions, data sets, examples, demos, and vignettes for the book Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York. ISBN 978-0-387-77316-2. (See the vignette "AER" for a package overview.)

This package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section in main memory.

This package provides primitives for visualizing distributions using ggplot2 that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized.

This package provides an extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for the special data format used for quantitative language comparison (QLC).

Publish data sets, models, and other R objects, making it easy to share them across projects and with your colleagues. You can pin objects to a variety of "boards", including local folders (to share on a networked drive or with DropBox), Posit Connect, AWS S3, and more.

This package provides a graphics device for R that is accessible via network protocols. This package was created to make it easier to embed live R graphics in integrated development environments and other applications. The included HTML/JavaScript client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. The device asynchronously serves graphics via HTTP and WebSockets'.

This package implements reinforcement learning environments and algorithms as described in Sutton & Barto (1998). The Q-Learning algorithm can be used with function approximation, eligibility traces (Singh & Sutton, 1996) and experience replay (Mnih et al., 2013).

This package provides basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999).

This package lets you build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines" <doi:10.1214/aos/1176347963>. The term "MARS" is trademarked and thus not used in the name of the package.

This package provides a set of signal processing functions originally written for Matlab and GNU Octave. It includes filter generation utilities, filtering functions, resampling routines, and visualization of filter models. It also includes interpolation functions.

This package provides the URL checking tools available in R 4.1+ as a package for earlier versions of R. It also uses concurrent requests so can be much faster than the serial versions.

The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption, gzip compression, authentication, and other libcurl goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces.

This package implements the diffusion map method of data parametrization, including creation and visualization of diffusion maps, clustering with diffusion K-means and regression using the adaptive regression model.

The generalised lambda distribution, or Tukey lambda distribution, provides a wide variety of shapes with one functional form. This package provides random numbers, quantiles, probabilities, densities and density quantiles for four different types of the distribution, the FKML (Freimer et al 1988), RS (Ramberg and Schmeiser 1974), GPD (van Staden and Loots 2009) and FM5 - see documentation for details. It provides the density function, distribution function, and Quantile-Quantile plots. It implements a variety of estimation methods for the distribution, including diagnostic plots. Estimation methods include the starship (all 4 types), method of L-Moments for the GPD and FKML types, and a number of methods for only the FKML type. These include maximum likelihood, maximum product of spacings, Titterington's method, Moments, Trimmed L-Moments and Distributional Least Absolutes.

This package provides helper functions to work with spreadsheets and the A1:D10 style of cell range specification.

This is a package for creating tiny yet beautiful documents and vignettes from R Markdown. The package provides the html_pretty output format as an alternative to the html_document and html_vignette engines that convert R Markdown into HTML pages. Various themes and syntax highlight styles are supported.

This package combines a forecast of a time series, using the function forecast, with the dynamic plots from dygraphs.

This package provides a collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in spdep.

This tool takes longitudinal dataset as input and analyzes if there is significant change of the features over time (a proxy for treatments), while detects and controls for covariates simultaneously. LongDat is able to take in several data types as input, including count, proportion, binary, ordinal and continuous data. The output table contains p values, effect sizes and covariates of each feature, making the downstream analysis easy.