clusterDiagGaussianNames: Create a vector of diagonal Gaussian mixture model names.

In MixAll: Clustering and Classification using Model-Based Mixture Models

Description

In a diagonal Gaussian mixture model, we assume that the variance matrices are diagonal in each cluster. Assumptions on the proportions and standard deviations give rise to 8 models:

1. The proportions can be equal or free.

2. The standard deviations can be equal or free for all the variables.

3. The standard deviations can be equal or free for all the clusters.

Usage

clusterDiagGaussianNames(prop = "all", sdInCluster = "all",
  sdBetweenCluster = "all")

clusterValidDiagGaussianNames(names)

Arguments

prop	A character string equal to "equal", "free" or "all". Default is "all".
sdInCluster	A character string equal to "equal", "free" or "all". Default is "all".
sdBetweenCluster	A character string equal to "equal", "free" or "all". Default is "all".
names	a vector of character

Details

The model names are summarized in the following array:

Model Name	Proportions	s.d. in variables	s.d. in clusters
gaussian_p_sjk	Equal	Free	Free
gaussian_p_sj	Equal	Free	Equal
gaussian_p_sk	Equal	Equal	Free
gaussian_p_s	Equal	Equal	Equal
gaussian_pk_sjk	Free	Free	Free
gaussian_pk_sj	Free	Free	Equal
gaussian_pk_sk	Free	Equal	Free
gaussian_pk_s	Free	Equal	Equal

Value

A vector of character with the model names.

Examples

clusterDiagGaussianNames()
## same as c("gaussian_p_sk", "gaussian_pk_sk")
clusterDiagGaussianNames(prop="all", sdInCluster="equal", sdBetweenCluster= "free")

MixAll documentation built on Sept. 12, 2019, 5:05 p.m.