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CondMVT: 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)<doi:10.3233/mas-200493>, and Kinyanjui, Tamba, and Okenye(2021)<http://www.ceser.in/ceserp/index.php/ijamas/article/view/6726/0> for more details.
Getting started
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Package details |
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| Author | Paul Kinyanjui [aut, cre], Cox Tamba [aut], Justin Okenye [aut], Luke Orawo [ctb] |
| Maintainer | Paul Kinyanjui <kinyanjui.access@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| Package repository | View on CRAN |
| Installation |
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