The lpSolveAPI package provides an R interface to lp_solve, a MILP, solver with support for pure linear, (mixed) integer/binary, semi-continuous and SOS models.

This package provides an extension to the Shiny web application framework for R, making it easy to create attractive dashboards.

This package provides fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. It provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.

This package provides tools for the calibration of penalized criteria for model selection. The calibration methods available are based on the slope heuristics.

This package provides a unified R graphics backend. Render R graphics fast and easy to many common file formats. It provides a thread safe C interface for asynchronous rendering of R graphics.

It contains functions that solve least squares linear regression problems under linear equality/inequality constraints. Functions for solving quadratic programming problems are also available, which transform such problems into least squares ones first.

This package provides five omnibus tests for testing the composite hypothesis of normality.

This package provides the usual distribution functions, maximum likelihood inference and model diagnostics for univariate stationary extreme value mixture models. Also, there are provided kernel density estimation including various boundary corrected kernel density estimation methods and a wide choice of kernels, with cross-validation likelihood based bandwidth estimator. Reasonable consistency with the base functions in the evd package is provided, so that users can safely interchange most code.

This package provides syntax highlighting for R source code. Currently it supports LaTeX and HTML output. Source code of other languages is supported via Andre Simon's highlight package.

This package provides fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen glue.

This package provides an implementation of the Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution".

This package provides alternative statistical methods for meta-analysis, including:

1. bivariate generalized linear mixed models for synthesizing odds ratios, relative risks, and risk differences

2. heterogeneity tests and measures that are robust to outliers;

3. measures, tests, and visualization tools for publication bias or small-study effects;

4. meta-analysis of diagnostic tests for synthesizing sensitivities, specificities, etc.;

5. meta-analysis methods for synthesizing proportions;

6. models for multivariate meta-analysis.

This package provides the cumulative distribution function (CDF), quantile, and statistical power calculator for a collection of thresholding Fisher's p-value combination methods, including Fisher's p-value combination method, truncated product method and, in particular, soft-thresholding Fisher's p-value combination method which is proven to be optimal in some context of signal detection. The p-value calculator for the omnibus version of these tests are also included.

In putative Transcription Factor Binding Sites (TFBSs) identification from sequence/alignments, we are interested in the significance of certain match scores. TFMPvalue provides the accurate calculation of a p-value with a score threshold for position weight matrices, or the score with a given p-value. It is an interface to code originally made available by Helene Touzet and Jean-Stephane Varre, 2007, Algorithms Mol Biol:2, 15. Touzet and Varre (2007).

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'.

Lp_solve is software for solving linear, integer and mixed integer programs. This implementation supplies a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems.

This package provides a collection of tests, data sets, and examples for diagnostic checking in linear regression models. Furthermore, some generic tools for inference in parametric models are provided.

This package provides functionality to dynamically define R functions and S4 methods with inlined C, C++ or Fortran code supporting .C and .Call calling conventions.

R-tgb provides Bayesian nonstationary regression and treed Gaussian processes. In addition, it provides visualization functions, tree drawing, sensitivity analysis, multi-resolution models, and sequential experimental design tools, including ALM, ALC, and expected improvement for optimizing noisy black-box functions.

This package performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. It includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.

This package abbreviates strings to a specified minimum number of characters, such that the strings remain unique (if they originally were).

This package provides software for the book Spectral Analysis for Physical Applications, Donald B. Percival and Andrew T. Walden, Cambridge University Press, 1993.

This package provides multiple sources of stopwords, for use in text analysis and natural language processing.

This package provides a small collection of interesting and educational machine learning data sets which are used as examples in the mlr3 book Applied machine learning using mlr3 in R https://mlr3book.mlr-org.com, the use case gallery https://mlr3gallery.mlr-org.com, or in other examples. All data sets are properly preprocessed and ready to be analyzed by most machine learning algorithms. Data sets are automatically added to the dictionary of tasks if mlr3 is loaded.