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CondMVT  

Conditional Multivariate t Distribution, Expectation Maximization Algorithm, and Its Stochastic Variants
View on CRAN: Click here


Download and install CondMVT package within the R console
Install from CRAN:
install.packages("CondMVT")

Install from Github:
library("remotes")
install_github("cran/CondMVT")

Install by package version:
library("remotes")
install_version("CondMVT", "0.1.0")



Attach the package and use:
library("CondMVT")
Maintained by
Paul Kinyanjui
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-28
Latest Update: 2022-06-28
Description:
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) for more details.
How to cite:
Paul Kinyanjui (2022). CondMVT: Conditional Multivariate t Distribution, Expectation Maximization Algorithm, and Its Stochastic Variants. R package version 0.1.0, https://cran.r-project.org/web/packages/CondMVT. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for CondMVT
Functions, R codes and Examples using the CondMVT R package
Some associated functions: CondMVT . EM_Umsteps . EM_Uonestep . EM_msteps . EM_onestep . MISS . SMCEM_Umsteps . SMCEM_Uonestep . SMCEM_msteps . SMCEM_onestep . dcmvt . pcmvt . rcmvt . 
Some associated R codes: CondMVT.R . EM_Umsteps.R . EM_Uonestep.R . EM_msteps.R . EM_onestep.R . MISS.R . SMCEM_Umsteps.R . SMCEM_Uonestep.R . SMCEM_msteps.R . SMCEM_onestep.R . dcmvt.R . pcmvt.R . rcmvt.R .  Full CondMVT package functions and examples
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