Multivariate Surrogate Synchrony ('mvSUSY') estimates the synchrony within datasets that contain more than two time series. 'mvSUSY' was developed from Surrogate Synchrony ('SUSY') with respect to implementing surrogate controls, and extends synchrony estimation to multivariate data. 'mvSUSY' works as described in Meier & Tschacher (2021).

Routines to perform estimation and inference under the multivariate
  t-distribution <doi:10.1007/s10182-022-00468-2>. Currently, the following methodologies 
  are implemented: multivariate mean and covariance estimation, hypothesis testing 
  about equicorrelation and homogeneity of variances, the Wilson-Hilferty transformation, 
  QQ-plots with envelopes and random variate generation.

Multivariate hypothesis tests and confidence intervals...

Functions to run fixed effects or random effects multivariate meta-analysis.

Computes multivariate normal and t probabilities, quantiles, random deviates, 
  and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae 
  parameterised by Cholesky factors of covariance or precision matrices are implemented 
  for interval-censored and exact data, or a mix thereof. Score functions for these 
  log-likelihoods are available. A class representing multiple lower triangular matrices 
  and corresponding methods are part of this package.

A function for plotting multivariate time series data.

Defines predict function that transforms output from a Tweedie
    Generalized Linear Mixed Model (using 'glmmTMB'),
    Generalized Additive Model (using 'mgcv'), or
    spatio-temporal Generalized Linear Mixed Model (using package 'tinyVAST'),
    and returns predicted proportions (and standard errors) across a
    grouping variable from an equivalent multivariate-logit Tweedie model.
    These predicted proportions can then be used for standard plotting
    and diagnostics.  See Thorson et al. 2022 <doi:10.1002/ecy.3637>.

Rudimentary functions for sampling and calculating density from the matrix-variate variance-gamma distribution.