This package provides functionality to benchmark your CPU and compare against other CPUs. Also provides functions for obtaining system specifications, such as RAM, CPU type, and R version.

Tidyft is an extension of data.table. It uses modifification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to tidyverse.

This package provides functions relating to time series analysis and computational finance.

This package provides helpers for reordering factor levels (including moving specified levels to front, ordering by first appearance, reversing, and randomly shuffling), and tools for modifying factor levels (including collapsing rare levels into other, "anonymizing", and manually "recoding").

This package provides a differential evolution (DE) stochastic algorithms for global optimization of problems with and without constraints. The aim is to curate a collection of its state-of-the-art variants that

1. do not sacrifice simplicity of design,

2. are essentially tuning-free, and

3. can be efficiently implemented directly in the R language.

In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The NNG-powered mirai R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a scheduler that efficiently processes these intense workloads. The crew package extends mirai with a unifying interface for third-party worker launchers.

This package provides miscellaneous functions for training and plotting classification and regression models.

This package provides various methods for clustering and cluster validation. For example, it provides fixed point clustering, linear regression clustering, clustering by merging Gaussian mixture components, as well as symmetric and asymmetric discriminant projections for visualisation of the separation of groupings.

This package lets you create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. It can parse various HTTP request bodies. It can send JSON data or files from the disk. It includes a web app that implements the httpbin.org web service.

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 efficient interface to MPI by utilizing S4 classes and methods with a focus on Single Program/Multiple Data (SPMD) parallel programming style, which is intended for batch parallel execution.

This package provides functions used to build R packages. It locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them.

This package provides a general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Functions for simulating and testing particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics.

This package allows you to control the number of threads the BLAS library uses. It is also possible to control the number of threads in OpenMP.

This package provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. It uses a trans-dimensional Markov Chain Monte Carlo (MCMC) approach based on a continuous-time birth-death process.

This package implements core utilities for single-cell RNA-seq data analysis. Contained within are utility functions for working with DE matrices and count matrices, a collection of functions for manipulating and plotting data via ggplot2, and functions to work with cell graphs and cell embeddings. Graph-based methods include embedding kNN cell graphs into a UMAP, collapsing vertices of each cluster in the graph, and propagating graph labels.

In putative Transcription Factor Binding Sites (TFBSs) identification from sequence/alignments, we are interested in the significance of certain match scores. TFMPvalue provides the accurate calculation of a p-value with a score threshold for position weight matrices, or the score with a given p-value. It is an interface to code originally made available by Helene Touzet and Jean-Stephane Varre, 2007, Algorithms Mol Biol:2, 15. Touzet and Varre (2007).

This package provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.

This package provides power analysis functions along the lines of Cohen (1988).

This package lets you use syntax inspired by the package glue to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.

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

This package provides authentication helpers for Snowflake. It provides compatibility with authentication approaches supported by the Snowflake Connector for Python and the Snowflake CLI.

This package provides a model agnostic tool for decomposition of predictions from black boxes. It supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models.

This package implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.