This is a deprecated package for accessing huge amounts of data. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), or BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix package.

This package provides functions that wrap popular phylogenetic software for sequence alignment, masking of sequence alignments, and estimation of phylogenies and ancestral character states.

Reshape2 is an R library to flexibly restructure and aggregate data using just two functions: melt and dcast (or acast).

This package provides a lightweight package to easily manipulate, clean, transform, and prepare your data for analysis. It also forms the data wrangling backend for the packages in the easystats ecosystem.

This package is a collection of functions and layers to enhance ggplot2. The flagship function is ggMarginal(), which can be used to add marginal histograms/boxplots/density plots to ggplot2 scatterplots.

The GNU Scientific Library (or GSL) is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The RcppGSL package provides an easy-to-use interface between GSL data structures and R using concepts from Rcpp which is itself a package that eases the interfaces between R and C++.

This package is for building isoscapes using mixed models and inferring the geographic origin of samples based on their isotopic ratios. This package is essentially a simplified interface to several other packages which implements a new statistical framework based on mixed models. It uses spaMM for fitting and predicting isoscapes, and assigning an organism's origin depending on its isotopic ratio. IsoriX also relies heavily on the package rasterVis for plotting the maps produced with terra using lattice'.

The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.

This package implements the fast cross-validation via sequential testing (CVST) procedure. CVST is an improved cross-validation procedure which uses non-parametric testing coupled with sequential analysis to determine the best parameter set on linearly increasing subsets of the data. Additionally to the CVST the package contains an implementation of the ordinary k-fold cross-validation with a flexible and powerful set of helper objects and methods to handle the overall model selection process. The implementations of the Cochran's Q test with permutations and the sequential testing framework of Wald are generic and can therefore also be used in other contexts.

This package provides an mlr3 extension that provides various resampling-based confidence interval (CI) methods for estimating the generalization error. These CI methods are implemented as mlr3 measures, enabling the evaluation of individual algorithms on specific tasks as well as the comparison of different learning algorithms.

This package provides visualizations for SHAP (SHapley Additive exPlanations) such as waterfall plots, force plots, various types of importance plots, dependence plots, and interaction plots. These plots act on a shapviz object created from a matrix of SHAP values and a corresponding feature dataset. Wrappers for the R packages xgboost, lightgbm, fastshap, shapr, h2o, treeshap, DALEX, and kernelshap are added for convenience. By separating visualization and computation, it is possible to display factor variables in graphs, even if the SHAP values are calculated by a model that requires numerical features. The plots are inspired by those provided by the shap package in Python, but there is no dependency on it.

This package provides header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <https://en.wikipedia.org/wiki/Hungarian_algorithm>; Kuhn (1955) <doi:10.1002/nav.3800020109>).

This is a package for drawing calibrated scales with tick marks on (non-orthogonal) variable vectors in scatterplots and biplots.

This is a package for interactive Reingold-Tilford tree diagrams created using D3.js, where every node can be expanded and collapsed by clicking on it. Tooltips and color gradients can be mapped to nodes using a numeric column in the source data frame.

This package provides a ggplot2 extension for drawing gene arrow maps.

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 support for measurement units in R vectors, matrices and arrays: automatic propagation, conversion, derivation and simplification of units; raising errors in case of unit incompatibility. It is compatible with the POSIXct, Date and difftime classes.

This package contains a list of functional time series, sliced functional time series, and functional data sets. Functional time series is a special type of functional data observed over time. Sliced functional time series is a special type of functional time series with a time variable observed over time.

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.

Tools to clean and process text. Tools are geared at checking for substrings that are not optimal for analysis and replacing or removing them (normalizing) with more analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf, & Richards (2001) doi:10.1006/csla.2001.0169) or extracting them into new variables. For example, emoticons are often used in text but not always easily handled by analysis algorithms. The replace_emoticon() function replaces emoticons with word equivalents.

This package simulates the process of installing a package and then attaching it. This is a key part of the devtools package as it allows you to rapidly iterate while developing a package.

This package provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain.

Phylogenetic trees generally contain multiple components including nodes, edges, branches and associated data. This package provides an approach to convert tree objects to tidy data frames. It also provides tidy interfaces to manipulate tree data.

The gdtools package provides functionalities to get font metrics and to generate base64 encoded string from raster matrix.