This package provides S3 classes and methods for one-dimensional normal mixture models, for, e.g., density estimation or clustering algorithms research and teaching; it provides the widely used Marron-Wand densities. It also provides tools for efficient random number generation and graphics.

This package provides a fast implementation of hierarchical clustering.

Written in C++ using Rcpp, this package provides a collection of metrics for evaluating models.

This package provides functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots.

This package provides a collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions.

This package implements beta regression for modeling beta-distributed dependent variables on the open unit interval (0, 1), e.g., rates and proportions, see Cribari-Neto and Zeileis (2010) <doi:10.18637/jss.v034.i02>. Moreover, extended-support beta regression models can accommodate dependent variables with boundary observations at 0 and/or 1. For the classical beta regression model, alternative specifications are provided: Bias-corrected and bias-reduced estimation, finite mixture models, and recursive partitioning for beta regression, see <doi:10.18637/jss.v048.i11>.

This package provides a collection of some tests commonly used for identifying outliers.

This package provides several layout algorithms to visualize networks which are not part of the igraph library. Most are based on the concept of stress majorization by Gansner et al. (2004) <doi:10.1007/978-3-540-31843-9_25>. Some more specific algorithms emphasize hidden group structures in networks or focus on specific nodes.

Several tools for assessing the quality of fit of a gaussian nonlinear model are provided.

This package provides an R wrapper to the Python natural language processing (NLP) library spaCy, from http://spacy.io.

This package runs a minimum-hypergeometric (mHG) test as described in "Discovering Motifs in Ranked Lists of DNA Sequences" by Eran Eden.

This package provides an implementation of dimensionality reduction via regression using Kernel Ridge Regression.

This package provides an R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). It also allows the combination of non-negative and non-positive constraints.

This package facilitates mapping by making natural earth map data from https://www.naturalearthdata.com/ more easily available to R users.

This package provides high level functions for parallel programming with Rcpp. For example, the parallelFor() function can be used to convert the work of a standard serial for loop into a parallel one and the parallelReduce() function can be used for accumulating aggregates or other values.

This package implements heuristics for the quadratic assignment problem (QAP). Currently only a simulated annealing heuristic is available.

This package computes and displays complex tables of summary statistics. Output may be in LaTeX, HTML, plain text, or an R matrix for further processing.

In S3 generics, it's useful to take ... so that methods can have additional arguments. But this flexibility comes at a cost: misspelled arguments will be silently ignored. The ellipsis package is an experiment that allows a generic to warn if any arguments passed in ... are not used.

This package provides an implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature.

Computes local polynomial estimators for the regression and also density. It comprises several different utilities to handle kernel estimators.

This package provides color schemes for maps (and other graphics) designed by Cynthia Brewer as described at http://colorbrewer2.org

This package provides an interface to Amazon Web Services cost management services, including cost and usage reports, budgets, pricing, and more.

This package provides functionality for client-side navigation of the server side file system in shiny apps. In case the app is running locally this gives the user direct access to the file system without the need to "download" files to a temporary location. Both file and folder selection as well as file saving is available.

This package provides functions for fitting the entire solution path of the Elastic-Net and also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed by the same function.