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.

This package provides functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. It was designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time.

The r-nleqslv package solves a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

Tools for integrating spatially-misaligned GIS datasets. Part of the Sub-National Geospatial Data Archive System.

The ade4 package contains data analysis functions to analyze ecological and environmental data in the framework of Euclidean exploratory methods.

This package provides an R wrapper for the special functions and quasi random number generators of the GNU Scientific Library.

Tidyft is an extension of data.table. It uses modifification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to tidyverse.

Make acoustic cues to use with the R package ndl. The package implements functions used in the PLoS ONE paper "Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit." doi:10.1371/journal.pone.0174623

This package provides tools to create pretty tables for HTML documents and other formats. Functions are provided to let users create tables, modify and format their content. It extends the officer package and can be used within R markdown documents when rendering to HTML and to Word documents.

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

This package supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward.

This package contains a simple SMTP client which provides a portable solution for sending email, including attachments, from within R.

This package implements easy-to-use functions to generate 2-7 sets Venn plot in publication quality. ggVennDiagram plot Venn using well-defined geometry dataset and ggplot2. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package venn. We provide internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in three components: set edges, set labels, and regions. From version 1.0, it is possible to customize these components as you demand in ordinary ggplot2 grammar.

The R kernel for the Jupyter environment executes R code which the front-end (Jupyter Notebook or other front-ends) submits to the kernel via the network.

Online data collection tools like Google Forms often export multiple-response questions with data concatenated in cells. The concat.split (cSplit) family of functions provided by this package splits such data into separate cells. This package also includes functions to stack groups of columns and to reshape wide data, even when the data are "unbalanced"---something which reshape (from base R) does not handle, and which melt and dcast from reshape2 do not easily handle.

This package provides conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.

This package facilitates RNA secondary structure plotting.

The gg.gap function enables you to define segments for the y-axis in a ggplot2 plot.

This package provides two methods of plotting categorical scatter plots such that the arrangement of points within a category reflects the density of data at that region, and avoids over-plotting.

Thisp package enables you to track and report code coverage for your package and (optionally) upload the results to a coverage service. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.

This package offers an implementation of the Abnormal blood profile score (ABPS). The ABPS is a part of the Athlete biological passport program of the World anti-doping agency, which combines several blood parameters into a single score in order to detect blood doping. The package also contains functions to calculate other scores used in anti-doping programs, such as the ratio of hemoglobin to reticulocytes (OFF-score), as well as example data.

This package helps you to automate R package and project setup tasks that are otherwise performed manually. This includes setting up unit testing, test coverage, continuous integration, Git, GitHub integration, licenses, Rcpp, RStudio projects, and more.

This package provides functions to convert R objects into JSON objects and vice-versa.

This package provides model selection tools and selfStart functions to fit parametric curves in the nls, nlsList and nlme frameworks.