This package implements the generalization of the Shapiro-Wilk test
        for multivariate normality proposed by Villasenor-Alva and
        Gonzalez-Estrada (2009).

An implementation of the alternating expectation conditional maximization (AECM) algorithm for matrix-variate variance gamma (MVVG) and normal-inverse Gaussian (MVNIG) linear models. These models are designed for settings of multivariate analysis with clustered non-uniform observations and correlated responses. The package includes fitting and prediction functions for both models, and an example dataset from a periodontal on Gullah-speaking African Americans, with responses in gaad_res, and covariates in gaad_cov. For more details on the matrix-variate distributions used, see Gallaugher & McNicholas (2019) <doi:10.1016/j.spl.2018.08.012>.

Fits multivariate Ornstein-Uhlenbeck types of models to continues trait data from species related by a common evolutionary history. See K. Bartoszek, J, Pienaar, P. Mostad, S. Andersson, T. F. Hansen (2012) <doi:10.1016/j.jtbi.2012.08.005> and K. Bartoszek, and J. Tredgett Clarke, J. Fuentes-Gonzalez, V. Mitov,  J. Pienaar, M. Piwczynski, R. Puchalka,  K. Spalik, K. L. Voje (2024) <doi:10.1111/2041-210X.14376>. The suggested PCMBaseCpp package (which significantly speeds up the likelihood calculations) can be obtained from <https://github.com/venelin/PCMBaseCpp/>.

Estimates the multivariate skew-t and nested models, as described in the
    articles Liseo, B., Parisi, A. (2013). Bayesian inference for the multivariate skew-normal
    model: a population Monte Carlo approach. Comput. Statist. Data Anal.
    <doi:10.1016/j.csda.2013.02.007> and in Parisi, A., Liseo, B. (2017). Objective Bayesian
    analysis for the multivariate skew-t model. Statistical Methods & Applications
    <doi: 10.1007/s10260-017-0404-0>.

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).