This package provides utility functions for easy parallelism in R. This includes some reexports from other packages, utility functions for splitting and parallelizing over blocks, and choosing and setting the number of cores used.

This package provides R functions implementing a standard unit testing framework, with additional code inspection and report generation tools.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.

This package provides different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.

This package contains functions to compute the nonparametric maximum likelihood estimator (MLE) for the bivariate distribution of (X,Y), when realizations of (X,Y) cannot be observed directly. To be more precise, we consider the situation where we observe a set of rectangles that are known to contain the unobservable realizations of (X,Y). We compute the MLE based on such a set of rectangles. The methods can also be used for univariate censored data (see data set cosmesis), and for censored data with competing risks (see data set menopause). The package also provides functions to visualize the observed data and the MLE.

This package provides a library for rolling windows operations. The package enables full control over the window length, window lag, and time indices. With a runner one can apply any R function on rolling windows. The package eases work with equally and unequally spaced time series.

The trimmed k-means clustering method by Cuesta-Albertos, Gordaliza and Matran (1997). This optimizes the k-means criterion under trimming a portion of the points.

This package includes functions to compute the area under the curve of selected measures: the area under the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the receiver operating characteristic curve (AUROC). The curves can also be visualized. Support for partial areas is provided.

This package checks adherence to a given style, syntax errors and possible semantic issues. It supports on the fly checking of R code edited with RStudio IDE, Emacs and Vim.

This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

This package provides plotting functions for posterior analysis, model checking, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling.

This package provides a collection of tools to make working with physical measurements easier. One can convert between metric and imperial units, or calculate a dimension's unknown value from other dimensions' measurements.

This package provides a programmatic deployment interface for RPubs, shinyapps.io, and RStudio Connect. Supported content types include R Markdown documents, Shiny applications, Plumber APIs, plots, and static web content.

This package provides functions for fitting and plotting SITAR growth curve models. SITAR is a shape- invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales.

This package contains functionality for performing the following methods of p-value aggregation: Fisher's method, the Lancaster method (weighted Fisher's method), and Sidak correction.

This package provides a fast match replacement for cases that require repeated look-ups. It is slightly faster that R's built-in match function on first match against a table, but extremely fast on any subsequent lookup as it keeps the hash table in memory.

This package provides a simple yet powerful logging utility. Based loosely on log4j, futile.logger takes advantage of R idioms to make logging a convenient and easy to use replacement for cat and print statements.

The goal of pak is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. pak has a dependency solver, so it finds version conflicts before performing the installation. This version of pak supports CRAN, Bioconductor and GitHub packages as well.

ACDm is a package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. It creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.

prospectr provides miscellaneous functions to preprocess spectroscopic data and conduct representative sample selection, or calibration sampling.

This package provides number-theoretic functions for factorization, prime numbers, twin primes, primitive roots, modular logarithm and inverses, extended GCD, Farey series and continued fractions. It includes Legendre and Jacobi symbols, some divisor functions, Euler's Phi function, etc.

This package provides tools to help working with text files. It can return the number of lines; print the first and last lines; convert encoding. Operations are made without reading the entire file before starting, resulting in good performances with large files.

This package provides an implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018). It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) is also provided.

Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.