calcloglik: Calculate log-likelihood for a Gaussian mixture model.

In markajoc/MBCbigP: Model-Based Clustering for High-Dimensional Data

Description

Calculate log-likelihood for a Gaussian mixture model.

Usage

calcloglik(x, pro, mean, sigma, groups)

calcloglik_split(x_A, x_B, pro, mean_A, mean_B, sigma_AA, sigma_AB, sigma_BB,
  groups)

logLik.mbcbigp(object, ...)

Arguments

x, x_A, x_B	A dataframe or matrix of data.
pro	A vector of mixing proportions.
mean, mean_A, mean_B	A 2-D array of mean vectors.
sigma, sigma_AA, sigma_AB, sigma_BB	A 3-D array of covariance matrices.
groups	The integer number of groups.
object	An object of class "mbcbigp"
...	not used

Value

A single numeric value.

markajoc/MBCbigP documentation built on May 30, 2019, 8:39 a.m.