permuteLabels: Mixed Membership Post-Processing

In mixedMem: Tools for Discrete Multivariate Mixed Membership Models

Description

Mixed Membership models are invariant to permutations of the sub-population labels; swapping the names of each sub-population yields an equivalent model. The ordering of the labels in a fitted model is dependent on the initialization points of the variational EM algorithim. The permuteLabels function returns a mixedMemModel object where the labels (for θ, φ, δ and α) have been permuted according a given permutation of the integers 1 through K. The findLabels function can be used to find a permutation of the labels which most closely matches another fitted model.

Usage

permuteLabels(model, perm)

Arguments

model	a fitted mixedMemModel object which will be relabeled.
perm	a vector of length K with integers 1:K. This is the permutation by which to relabel the mixedMemModel object such that group i in the returned mixedMemModel object corresponds to group perm[i] from the input mixedMemModel object.

Value

permuteLabels returns a mixedMemModel object such that group i in the returned mixedMemModel object corresponds to group perm[i] from the input mixedMemModel object

See Also

findLabels

mixedMem documentation built on Dec. 2, 2020, 1:09 a.m.