This package models with sparse and dense matrix matrices, using modular prediction and response module classes.

This package provides an implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.

This package provides an R interface to the Spectra library for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n.

This package provides weighted frequency and contingency tables of categorical variables and of the comparison of the mean value of a numerical variable by the levels of a factor, and methods to produce xtable objects of the tables and to plot them. There are also functions to facilitate the character encoding conversion of objects, to quickly convert fixed width files into CSV ones, and to export a data.frame to a text file with the necessary R and SPSS codes to reread the data.

This package provides sparse vectors powered by ALTREP (Alternative Representations for R Objects) that behave like regular vectors, and can thus be used in data frames. It also provides tools to convert between sparse matrices and data frames with sparse columns and functions to interact with sparse vectors.

This package implements readers and writers for file formats associated with genetics data. Reading and writing Plink BED/BIM/FAM and GCTA binary GRM formats is fully supported, including a lightning-fast BED reader and writer implementations. Other functions are readr wrappers that are more constrained, user-friendly, and efficient for these particular applications; handles Plink and Eigenstrat tables (FAM, BIM, IND, and SNP files). There are also make functions for FAM and BIM tables with default values to go with simulated genotype data.

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 provides a collection of functions to create spatial weights matrix objects from polygon contiguities, from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree.

This package provides a utility for R to parse a bibtex file.

This package provides tools for the computation of the matrix exponential, logarithm, square root, and related quantities.

Phangorn is a package for phylogenetic analysis in R. It supports estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation.

This package provides a menu-driven program and library of functions for carrying out convergence diagnostics and statistical and graphical analysis of Markov chain Monte Carlo (MCMC) sampling output.

This package performs 2D Delaunay triangulation, constrained or unconstrained, with the help of the C++ library CDT. A function to plot the triangulation is provided. The constrained Delaunay triangulation has applications in geographic information systems.

This package provides a wrapper for the homologene database by the National Center for Biotechnology Information (NCBI). It allows searching for gene homologs across species. The package also includes an updated version of the homologene database where gene identifiers and symbols are replaced with their latest (at the time of submission) version and functions to fetch latest annotation data to keep updated.

For distributions whose probability density functions are log-concave, the adaptive rejection sampling algorithm can be used to build envelope functions for sampling. For others, the modified adaptive rejection sampling algorithm, the concave-convex adaptive rejection sampling algorithm, and the adaptive slice sampling algorithm can be used. This R package mainly includes these four functions: rARS(), rMARS(), rCCARS(), and rASS(). These functions can realize sampling based on the algorithms above.

This package provides a comprehensive collection of color palettes, color maps, and tools to evaluate them.

This r-physicalactivity package provides a function wearingMarking for classification of monitored wear and nonwear time intervals in accelerometer data collected to assess physical activity. The package also contains functions for making plots of accelerometer data and obtaining the summary of various information including daily monitor wear time and the mean monitor wear time during valid days. The revised package version 0.2-1 improved the functions regarding speed, robustness and add better support for time zones and daylight saving. In addition, several functions were added:

1. the markDelivery can classify days for ActiGraph delivery by mail;

2. the markPAI can categorize physical activity intensity level based on user-defined cut-points of accelerometer counts.

It also supports importing ActiGraph (AGD) files with readActigraph and queryActigraph functions.

These utilities facilitate the programmatic manipulations of formulas, expressions, calls, assignments and other R language objects. These objects all share the same structure: a left-hand side, operator and right-hand side. This package provides methods for accessing and modifying this structures as well as extracting and replacing names and symbols from these objects.

This package reads and writes data files like CSV, TSV and FWF. When reading it uses a quick initial indexing step, then reads the values lazily, so only the data you actually use needs to be read. The writer formats the data in parallel and writes to disk asynchronously from formatting.

This small library contains a series of simple tools for constructing and manipulating confounded and fractional factorial designs.

This package provides a collection of ggplot2 color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows.

This package provides functions to fit Gaussian linear model by maximising the residual log likelihood where the covariance structure can be written as a linear combination of known matrices. It can be used for multivariate models and random effects models. It aims to provide an easy straight forward manner to specify random effects models, including random interactions. The code is optimized to use Sherman Morrison Woodbury identities for matrix inversion in random effects models.

This package implements various procedures for finding multiple change-points. Two methods make use of dynamic programming and pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change-points as well as other summary information.

The zlog package offers functions to transform laboratory measurements into standardised z or z(log)-values. Therefore the lower and upper reference limits are needed. If these are not known they could be estimated from a given sample.