Gaussian RPMM Split Criterion: Level-Weighted BIC

Description

Split criterion function: use a level-weighted version of BIC to determine split; there is an additional penalty incorporated for deep recursion.

Usage

1
glcSplitCriterionLevelWtdBIC(llike1, llike2, weight, ww, J, level)

Arguments

llike1

one-class likelihood.

llike2

two-class likelihood.

weight

weights from RPMM node.

ww

“ww” from RPMM node.

J

Number of items.

level

Node level.

Details

This is a function of the form “glcSplitCriterion...”, which is required to return a list with at least a boolean value split, along with supporting information. See glcTree for example of using “glcSplitCriterion...” to control split.

Value

bic1

One-class BIC, with additional penalty for deeper levels

bic2

Two-class BIC, with additional penalty for deeper levels

split

TRUE=split the node, FALSE=do not split the node.

See Also

glcSplitCriterionBIC, glcSplitCriterionBICICL, glcSplitCriterionJustRecordEverything, glcSplitCriterionLRT

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