Conditional Multivariate t Distribution, Expectation Maximization Algorithm, and Its Stochastic Variants

Computes conditional multivariate t probabilities, random deviates, and densities. It can also be used to create missing values at random in a dataset, resulting in a missing at random (MAR) mechanism. Inbuilt in the package are the Expectation-Maximization (EM), Monte Carlo EM, and Stochastic EM algorithms for imputation of missing values in datasets assuming the multivariate t distribution. See Kinyanjui, Tamba, Orawo, and Okenye (2020), and Kinyanjui, Tamba, and Okenye(2021)< http://www.ceser.in/ceserp/index.php/ijamas/article/view/6726/0> for more details.


CondMVT.package

Data Imputation in Multivariate t-Distribution Using EM, SEM, and MCEM Techniques.

Reference manual

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install.packages("CondMVT")

0.1.1 by Paul Kinyanjui, a year ago


Browse source code at https://github.com/cran/CondMVT


Authors: Paul Kinyanjui [aut, cre] , Cox Tamba [aut] , Justin Okenye [aut] , Luke Orawo [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports stats, mvtnorm


See at CRAN