glcSplit {RPMM}R Documentation

Gaussian Latent Class Splitter

Description

Splits a data set into two via a Gaussian mixture models

Usage

glcSplit(x, initFunctions, weight = NULL, index = NULL, level =
                 0, wthresh = 1e-09, verbose = TRUE, nthresh = 5,
                 splitCriterion = glcSplitCriterionBIC)

Arguments

x Data matrix (n x j) on which to perform clustering
initFunctions List of functions of type “glcInitialize...” for initializing latent class model. See glcInitializeFanny for an example of arguments and return values.
weight Weight corresponding to the indices passed (see index). Defaults to 1 for all indices
index Row indices of data matrix to include. Defaults to all (1 to n).
level ~~Describe level here~~
wthresh Weight threshold for filtering data to children. Indices having weight less than this value will not be passed to children nodes.
verbose Level of verbosity. Default=2 (too much). 0 for quiet.
nthresh Total weight in node required for node to be a candidate for splitting. Nodes with weight less than this value will never split.
splitCriterion Function of type “glcSplitCriterion...” for determining whether split should occur. See glcSplitCriterionBIC for an example of arguments and return values.

Details

Should not be called by user.

Value

A list of objects representing split.


[Package RPMM version 1.05 Index]