permuteLabels

a fitted <code>mixedMemModel</code> object which will be relabeled.

model

a vector of length K with integers 1:K. This is the permutation by which to relabel the <code>mixedMemModel</code> object such that
group i in the returned mixedMemModel object corresponds to group <code>perm</code>[i] from the input mixedMemModel object.

perm


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 <code>permuteLabels</code> function returns a <code>mixedMemModel</code> object where the labels (for $\theta$, $\phi$, $\delta$ and $\alpha$) have been permuted
according a given permutation of the integers 1 through K. The <code>findLabels</code> function can be used to find a permutation of the labels which
most closely matches another fitted model.


Fits mixed membership models with discrete multivariate data (with
or without repeated measures) following the general framework of Erosheva et al
(2004). This package uses a Variational EM approach by approximating the
posterior distribution of latent memberships and selecting hyperparameters
through a pseudo-MLE procedure. Currently supported data types are
Bernoulli, multinomial and rank (Plackett-Luce). The extended GoM model with fixed stayers from Erosheva et al     (2007) is now also supported. See Airoldi et al (2014) for other examples of mixed membership models.

permuteLabels: Mixed Membership Post-Processing

Description

Usage

Arguments

Value

See Also