maximisation_mv

data

(matrix): The probability weight matrix.

weights

(list): The list of sigma (co-variance matrices).

sigma

prior

(numeric): The number of clusters.

num_clusters

(numeric): The total number of observations in the data.

num_data

Calculates meu, sigma and prior based on the updated probability weight matrix.

Implements the Improved Expectation Maximisation EM* and the traditional EM algorithm for clustering
big data (gaussian mixture models for both multivariate and univariate datasets). This version
implements the faster alternative-EM* that expedites convergence via structure based data segregation.
The implementation supports both random and K-means++ based initialization. Reference: Parichit Sharma,
Hasan Kurban, Mehmet Dalkilic (2022) <doi:10.1016/j.softx.2021.100944>. Hasan Kurban,
Mark Jenne, Mehmet Dalkilic (2016) <doi:10.1007/s41060-017-0062-1>.

maximisation_mv: maximisation_mv: Part of DCEM package.

Description

Usage

Arguments

Value