This package orders panels in scatterplot matrices and parallel coordinate displays by some merit index. It contains various indices of merit, ordering functions, and enhanced versions of pairs and parcoord which color panels according to their merit level.

This package provides functions for phylocom integration, community analyses, null-models, traits and evolution. It implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010).

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.

The Ziggurat pseudo-random number generator (or PRNG) offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from C/C++ code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package.

This package helps to construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, and others. In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as a fallback solution.

This package provides an interface to the rich display capabilities of Jupyter front-ends (e.g. Jupyter Notebook). It is designed to be used from a running IRkernel session.

This package provides a simple git client for R based on libgit2 with support for SSH and HTTPS remotes. All functions in gert use basic R data types (such as vectors and data-frames) for their arguments and return values. User credentials are shared with command line git through the git-credential store and SSH keys stored on disk or ssh-agent.

This package allows you to create Q-Q and Manhattan plots for GWAS data from PLINK results.

This package provides tools to obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. It can be used to compute contrasts or linear functions of EMMs, trends, and comparisons of slopes.

This package implements reinforcement learning environments and algorithms as described in Sutton & Barto (1998). The Q-Learning algorithm can be used with function approximation, eligibility traces (Singh & Sutton, 1996) and experience replay (Mnih et al., 2013).

This package provides a replacement and extension of the optim function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that the function optimr was prepared to simplify the incorporation of minimization codes going forward. This package also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here.

This package provides the Open Source Geometry Engine (GEOS) as a C API that can be used to write high-performance C and C++ geometry operations using R as an interface. Headers are provided to make linking to and using these functions from C++ code as easy and as safe as possible. This package contains an internal copy of the GEOS library to guarantee the best possible consistency on multiple platforms.

Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015)

This package provides functions for creating plots and image files in a unified way regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default device options as well as scales and aspect ratios are controlled in a uniform way across all device types. Switching output format requires minimal changes in code. This package is ideal for large-scale batch processing, because it will never leave open graphics devices or incomplete image files behind, even on errors or user interrupts.

This package provides a series of additional Tcl commands and Tk widgets with style and various functions to supplement the tcltk package

Tidygeocoder makes getting data from geocoding services easy. A unified high-level interface is provided for a selection of supported geocoding services and results are returned in tibble format.

This package provides non-statistical utilities used by the software developed by the Statnet Project.

This package allows for data objects in R to be rendered as HTML tables using the JavaScript library DataTables (typically via R Markdown or Shiny). The DataTables library has been included in this R package.

The R kernel for the Jupyter environment executes R code which the front-end (Jupyter Notebook or other front-ends) submits to the kernel via the network.

This package provides a replacement for the extract function from the raster package that is suitable for extracting raster values using sf polygons.

This package lets you construct Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Results Data objects. These objects are used and re-used to construct summary tables, visualizations, and written reports. The package also exports utilities for working with these objects and creating new Analysis Results Data objects.

The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.

This is an R package for dimension reduction based on finite Gaussian mixture modeling of inverse regression.

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