This package contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library. All models return coda mcmc objects that can then be summarized using the coda package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.

This package provides tools for determining estimability of linear functions of regression coefficients, and epredict methods that handle non-estimable cases correctly.

This package is an implementation of a regularized regression prediction and empirical Bayes method to recover the true gene expression profile in noisy and sparse single-cell RNA-seq data. In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. This package single-cell analysis via expression recovery (SAVER) implements an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.

This is a package for the manipulation of genetic data (SNPs). Computation of genetic relationship matrix (GRM) and dominance matrix, linkage disequilibrium (LD), and heritability with efficient algorithms for linear mixed models (AIREML).

This package provides a wrapper around the Parsing Expression Grammar Template Library, a C++11 library for generating parsing expression grammars, that makes it accessible within Rcpp. With this, developers can implement their own grammars and easily expose them in R packages.

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

This package provides functionality for random generation of spatial data in the spatstat family of packages. It generates random spatial patterns of points according to many simple rules (complete spatial randomness, Poisson, binomial, random grid, systematic, cell), randomised alteration of patterns (thinning, random shift, jittering), simulated realisations of random point processes (simple sequential inhibition, Matern inhibition models, Matern cluster process, Neyman-Scott cluster processes, log-Gaussian Cox processes, product shot noise cluster processes) and simulation of Gibbs point processes (Metropolis-Hastings birth-death-shift algorithm, alternating Gibbs sampler).

This package provides functions to fit kernel density functions to animal activity time data; plot activity distributions; quantify overall levels of activity; statistically compare activity metrics through bootstrapping; and evaluate variation in linear variables with time (or other circular variables).

Thisp package enables you to track and report code coverage for your package and (optionally) upload the results to a coverage service. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.

The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. The ggraph package is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.

This package provides infrastructure to accurately measure and compare the execution time of R expressions.

The encoding of color can be handled in many different ways, using different color spaces. As different color spaces have different uses, efficient conversion between these representations are important. This package provides a set of functions that gives access to very fast color space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the convertColor function in the grDevices package.

This is a deprecated package for calculating pairwise multiple comparisons of mean rank sums. This package is superseded by the novel PMCMRplus package. The PMCMR package is no longer maintained, but kept for compatibility of dependent packages for some time.

This package estimates the parameters in Dirichlet-Multinomial and computes log-likelihoods.

OOMPA offers R packages for gene expression and proteomics analysis. OOMPA uses S4 classes to construct object-oriented tools with a consistent user interface. All higher level analysis tools in OOMPA are compatible with the eSet classes defined in BioConductor. The lower level processing tools offer an alternative to parts of BioConductor, but can also be used to enhance existing BioConductor packages.

R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off.

This package extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.

This package provides functions for prior and likelihood sensitivity analysis in Bayesian models. It implements methods to determine the sensitivity of the posterior to power-scaling perturbations of the prior and likelihood.

This package provides functions for bitwise operations on integer vectors.

Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.

This tool provides methods for aggregating ranked lists, especially lists of genes. It implements the Robust Rank Aggregation and other simple algorithms for the task. RRA method uses a probabilistic model for aggregation that is robust to noise and also facilitates the calculation of significance probabilities for all the elements in the final ranking.

Enrich your ggplots with group-wise comparisons. This package provides an easy way to indicate if two groups are significantly different. Commonly this is shown by a bracket on top connecting the groups of interest which itself is annotated with the level of significance. The package provides a single layer that takes the groups for comparison and the test as arguments and adds the annotation to the plot.

This package provides a set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides an extension to the Shiny web application framework for R, making it easy to create attractive dashboards.