This light-weight package helps you track and visualize the progress of parallel versions of vectorized R functions of the mc*apply family.

This is an unofficial package aimed at automating the import of LISREL output in R.

This package does local optimization using two derivatives and trust regions. Guaranteed to converge to local minimum of objective function.

The ROI is a framework for handling optimization problems in R.

This package provides a framework to create Bootstrap 3 HTML reports from knitr Rmarkdown.

This package offers a flexible, feature-rich yet light-weight logging framework based on R6 classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, JSON, (rotating) files, memory buffers, and databases, as well as email and push notifications.

This package provides utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data.

This package provides a custom CSS/HTML or GIF/image file for the loading screen in R Shiny. It also can use the marquee to have a custom text loading screen.

This package provides a %dopar% adapter such that any type of futures can be used as backends for the foreach framework.

This package provides an R library to generate Sankey network graphs in R and Shiny via the D3 visualization library.

This package provides a convenient tool to install and update Bioconductor packages.

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 methods for cluster analysis. It is a much extended version of the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".

This package provides tools used by organizational researchers for the analysis of multilevel data. It includes four broad sets of tools.

1. functions for estimating within-group agreement and reliability indices.

2. functions for manipulating multilevel and longitudinal (panel) data.

3. simulations for estimating power and generating multilevel data.

4. miscellaneous functions for estimating reliability and performing simple calculations and data transformations.

This package provides an implementation of evaluation metrics in R that are commonly used in supervised machine learning. It implements metrics for regression, time series, binary classification, classification, and information retrieval problems. It has zero dependencies and a consistent, simple interface for all functions.

This package provides a native R plotting library that provides a flexible declarative interface for creating interactive web-based graphics, backed by the Bokeh visualization library.

This package provides an R interface to the QuickJS portable JavaScript engine. The engine is bundled entirely within the package, requiring no external system dependencies beyond a C compiler.

This package provides functions for estimating tolerance limits (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings (linear regression, nonlinear regression, nonparametric regression, and multivariate regression), and analysis of variance tolerance intervals. Visualizations are also available for most of these settings.

Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data (Sellers & Shmueli, 2010) <doi:10.1214/09-AOAS306>. The package provides functions for model estimation, dispersion testing, and diagnostics. Zero-inflated CMP regression (Sellers & Raim, 2016) <doi:10.1016/j.csda.2016.01.007> is also supported.

This package provides a wrapper around the Parsing Expression Grammar Template Library, a C++11 library for generating parsing expression grammars, that makes it accessible within Rcpp. With this, developers can implement their own grammars and easily expose them in R packages.

This package implements shadowtextGrob() for grid and geom_shadowtext() layer for ggplot2. These functions draw text grob with background shadow.

This package provides the tools necessary to do non-standard evaluation (NSE) in R.

This package provides a Database Interface (DBI) compliant driver for R to access PostgreSQL database systems.

This package contains a function to do exact Hardy-Weinburg testing (using Fisher's test) for SNP genotypes as typically obtained in a Genome Wide Association Study (GWAS).