fit.mvn.miss.impute

split_data

<p>List containing the `mean` and `cov`.</p>

theta

<p>Imputation for a Single Component Multivariate Normal with Missingness.</p>

Parameter estimation and classification for Gaussian Mixture Models (GMMs) in the presence of missing data. This package uses an expectation conditional maximization algorithm to obtain maximum likelihood estimates for all model parameters and maximum a posteriori classifications of the input vectors. For additional details, please see McCaw ZR, Julienne H, Aschard H. "MGMM: an R package for fitting Gaussian Mixture Models on Incomplete Data." <doi:10.1101/2019.12.20.884551>.

fit.mvn.miss.impute: Imputation for a Single Component Multivariate Normal with Missingness.

Description

Usage

Arguments

Value