Provides samplers for various matrix variate distributions: Wishart, inverse-Wishart, normal, t, inverted-t, Beta type I, Beta type II, Gamma, confluent hypergeometric. Allows to simulate the noncentral Wishart distribution without the integer restriction on the degrees of freedom.

Creates an object that stores a matrix ensemble, matrices
  that share the same common properties, where rows and columns can be
  annotated. Matrices must have the same dimension and dimnames. Operators to
  manipulate these objects are provided as well as mechanisms to apply
  functions to these objects.

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds().  Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.  There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

Tests for block-diagonal structure in symmetric matrices (e.g. correlation matrices) under the null hypothesis of exchangeable off-diagonal elements. As described in Segal et al. (2019), these tests can be useful for construct validation either by themselves or as a complement to confirmatory factor analysis. Monte Carlo methods are used to approximate the permutation p-value with Hubert's Gamma (Hubert, 1976) and a t-statistic. This package also implements the chi-squared statistic described by Steiger (1980). Please see Segal, et al. (2019) <doi:10.1007/s11336-018-9647-4> for more information.

Functions to perform fast statistical hypothesis tests on rows/columns of matrices.
  The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use,
  3) compatibility with tests implemented in R (like those available in the 'stats' package).

An implementation of matrix mathematics wherein operations are performed "by name."

Provides functions to collapse a tidy data frame into matrices in a data frame
    and expand a data frame of matrices into a tidy data frame.