This package provides tools and functions for parsing, rendering and operating on semantic version strings. Semantic versioning is a simple set of rules and requirements that dictate how version numbers are assigned and incremented as outlined at http://semver.org.

This package provides a set of Shiny apps for effective communication and understanding in statistics. The current version includes properties of normal distribution, properties of sampling distribution, one-sample z and t tests, two samples independent (unpaired) t test and analysis of variance.

This package provides features to build gradient color maps.

The r-abd package contains data sets and sample code for the Analysis of biological data by Michael Whitlock and Dolph Schluter.

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 functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).

This package provides basic I/O tools for streaming and data parsing.

This package provides tools to integrate nucleotide sequencing data (variant call format, e.g. VCF or BCF) or meta-analysis results in R.

This package performs estimation of physical activity and sedentary behavior variables from activPAL events files.

This package lets you compute the median ranking according to Kemeny's axiomatic approach. Rankings can or cannot contain ties, rankings can be both complete or incomplete. The package contains both branch-and-bound algorithms and heuristic solutions recently proposed. The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties. The package also provides some useful utilities for deal with preference rankings, including both element-weight Kemeny distance and correlation coefficient.

This package contains an efficient implementation of Sen's slope method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) pre-whitening approaches to determining trends in climate data.

This package provides functions for obtaining the density, random variates and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and their mixture distribution.

The aim of SHAPforxgboost is to aid in visual data investigations using SHAP (Shapley additive explanation) visualization plots for XGBoost. It provides summary plot, dependence plot, interaction plot, and force plot. It relies on the XGBoost package to produce SHAP values.

This is a package supporting the analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

This package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive lasso, PLS, and Ridge Regression. In addition, the package provides model selection for lasso, adaptive lasso and Ridge regression based on cross-validation.

Create and customize interactive maps using the Leaflet JavaScript library and the htmlwidgets package. These maps can be used directly from the R console, from RStudio, in Shiny applications and R Markdown documents.

This package processes accelerometer data from uni-axial and tri-axial devices and generates data summaries. Also, includes functions to plot, analyze, and simulate accelerometer data.

This package provides an implementation of scatter plots for plotting. a three dimensional point cloud.

Phylogenetic clustering (phyloclustering) is an evolutionary continuous time Markov Chain model-based approach to identify population structure from molecular data without assuming linkage equilibrium. The package phyclust provides a convenient implementation of phyloclustering for DNA and SNP data, capable of clustering individuals into subpopulations and identifying molecular sequences representative of those subpopulations. It is designed in C for performance and interfaced with R for visualization.

This package contains functions useful for data screening, testing moderation, mediation and estimating power.

This package implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation estimation of the error can be done.

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 provides a tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. The package mainly revolves around two types of functions: Functions that find (the names of) information, starting with find_, and functions that get the underlying data, starting with get_. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.

This package provides functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.