This package provides tools to compute Gower's distance (or similarity) coefficient between records, and to compute the top-n matches between records. Core algorithms are executed in parallel on systems supporting OpenMP.

This package provides utilities to work with indices of effect size and standardized parameters for a wide variety of models, allowing computation and conversion of indices such as Cohen's d, r, odds, etc.

This package provides a compendium of new geometries, coordinate systems, statistical transformations, scales and fonts for ggplot2, including splines, 1d and 2d densities, univariate average shifted histograms, a new map coordinate system based on the PROJ.4-library along with geom_cartogram() that mimics the original functionality of geom_map(), formatters for "bytes", a stat_stepribbon() function, increased plotly compatibility and the StateFace open source font ProPublica. Further new functionality includes lollipop charts, dumbbell charts, the ability to encircle points and coordinate-system-based text annotations.

This package provides a cross between a 2D density plot and a scatter plot, implemented as a ggplot2 geom. Points in the scatter plot are colored by the number of neighboring points. This is useful to visualize the 2D-distribution of points in case of overplotting.

This package provides a set of tools for post processing the outcomes of species distribution modeling exercises. It includes novel methods for comparing models and tracking changes in distributions through time. It further includes methods for visualizing outcomes, selecting thresholds, calculating measures of accuracy and landscape fragmentation statistics, etc.

This package provides a computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available.

This package provides David Scott's ASH routines ported from S-PLUS to R.

Designed to enable simultaneous substitution in strings in a safe fashion. Safe means it does not rely on placeholders (which can cause errors in same length matches).

This package enables conversions between R objects and JavaScript Object Notation (JSON) using the rapidjsonr library.

This package provides efficient routines for manipulation of date-time objects while accounting for time-zones and daylight saving times. The package includes utilities for updating of date-time components (year, month, day etc.), modification of time-zones, rounding of date-times, period addition and subtraction etc. Parts of the CCTZ source code, released under the Apache 2.0 License, are included in this package.

This package provides tools for capturing logic in a Shiny app and exposing it as code that can be run outside of Shiny (e.g., from an R console). It also provides tools for bundling both the code and results to the end user.

A workflow is an object that can bundle together your pre-processing, modeling, and post-processing requests. For example, if you have a recipe and parsnip model, these can be combined into a workflow. The advantages are:

1. You don’t have to keep track of separate objects in your workspace.

2. The recipe prepping and model fitting can be executed using a single call to fit().

3. If you have custom tuning parameter settings, these can be defined using a simpler interface when combined with tune.

4. In the future, workflows will be able to add post-processing operations, such as modifying the probability cutoff for two-class models.

This package provides an R interface to V8: Google's JavaScript and WebAssembly engine.

This package provides various methods for MRI tissue classification.

This package implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices.

This package provides a set of tools for manipulating and reading geographic data, in particular ESRI Shapefiles. It includes binary access to GSHHG shoreline files. The package also provides interface wrappers for exchanging spatial objects with other R packages.

This package provides basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999).

This package provides an interface to the NetCDF file formats designed by Unidata for efficient storage of array-oriented scientific data and descriptions. Most capabilities of NetCDF version 4 are supported. Optional conversions of time units are enabled by UDUNITS version 2, also from Unidata.

This package computes optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.

This package provides a comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e. mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g. due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g. due to phylogenetic relatedness) can also be conducted.

Circle Manhattan Plot is an R package that can lay out genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals. Additional functions include: highlight signals, a group of SNPs, chromosome visualization and candidate genes around SNPs.

This package provides support for simple features, a standardized way to encode spatial vector data. It binds to GDAL for reading and writing data, to GEOS for geometrical operations, and to PROJ for projection conversions and datum transformations.

This package provides a variety of descriptive multivariate analyses with the singular value decomposition, such as principal components analysis, correspondence analysis, and multidimensional scaling. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

This package simplifies custom CSS styling of both shiny and rmarkdown via Bootstrap Sass. It supports both Bootstrap 3 and 4 as well as their various Bootswatch themes. An interactive widget is also provided for previewing themes in real time.