This package provides computationally efficient tools related to the multivariate normal and Student's t distributions. The main functionalities are: simulating multivariate random vectors, evaluating multivariate normal or Student's t densities and Mahalanobis distances. These tools are developed using C++ code and of the OpenMP API.

This package provides an R Markdown format for converting an R Markdown document to a grid-oriented dashboard. The dashboard flexibly adapts the size of its components to the containing web page.

This package provides functions useful in the design and ANOVA of experiments. The content falls into the following groupings:

1. data,

2. factor manipulation functions,

3. design functions,

4. ANOVA functions,

5. matrix functions,

6. projector and canonical efficiency functions, and

7. miscellaneous functions.

There is a vignette called DesignNotes describing how to use the design functions for randomizing and assessing designs. The ANOVA functions facilitate the extraction of information when the Error function has been used in the call to aov.

This package provides an implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018). It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) is also provided.

This package provides a simple method for representing a visual scene as it may be seen by an animal with less acute vision.

This package provides functionality to define and train neural networks similar to PyTorch but written entirely in R using the libtorch library. It also supports low-level tensor operations and GPU acceleration.

In Shiny apps, it is sometimes useful to store information on a particular item in a tooltip. Prompter allows you to easily create such tooltips, using Hint.css.

This package contains utility functions for the spatstat package which may also be useful for other purposes.

Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled.

This package provides an R interface to the Tabler HTML template. tablerDash is a light Bootstrap 4 dashboard template. There are different layouts available such as a one page dashboard or a multi-page template, where the navigation menu is contained in the navigation bar.

This package provides SNP array data from different types of copy-number regions. These regions were identified manually by the authors of the package and may be used to generate realistic data sets with known truth.

This package provides functionality to create pretty word clouds, visualize differences and similarity between documents, and avoid over-plotting in scatter plots with text.

This package infers directional Conservative causal core (gene) networks (C3NET). This is a version of the algorithm C3NET with directional network.

This package provides high performance container data types such as queues, stacks, deques, dicts and ordered dicts.

This package provides simple utility functions to read from and write to the system clipboards.

The glmnet package provides efficient procedures for fitting the entire lasso or elastic-net regularization path for linear and Poisson regression, as well as logistic, multinomial, Cox, multiple-response Gaussian and grouped multinomial models. The algorithm uses cyclical coordinate descent in a path-wise fashion.

This package lets you calculate power for generalized linear mixed models, using simulation. It was designed to work with models fit using the lme4 package. The package is described in Green and MacLeod (2016).

This package provides functions for manipulation of R documentation objects, including functions reprompt() and ereprompt() for updating Rd documentation for functions, methods and classes; it also includes Rd macros for citations and import of references from bibtex files for use in Rd files and roxygen2 comments, as well as many functions for manipulation of references and Rd files.

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 embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine is included.

This package provides a set of predicates and assertions for checking the properties of strings. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

This package provides functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.

This package provides improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.