computeBIC: Compute the approximate BIC

In mixedMem: Tools for Discrete Multivariate Mixed Membership Models

Description

computeBIC computes the approximate BIC of a given mixedMemModel, where the lower bound on the log-likelihood (also called ELBO) is used instead of the intractable true log-likelihood.

Usage

computeBIC(model)

Arguments

model

the mixedMemModel object for which the BIC will be calculated.

Details

BIC = -2 ELBO + p \log(Total)

where p is the number of estimated parameters and Total is the number of individuals in the sample.

This BIC model selection criteria is used in Erosheva et al (2007). The number of estimated parameters P includes the parameters θ and α, but omits the variational parameters φ and δ.

Value

computeBIC returns the approximate BIC value, a real number.

References

Erosheva, E. A., Fienberg, S. E., & Joutard, C. (2007). Describing disability through individual-level mixture models for multivariate binary data. The annals of applied statistics, 1(2), 346.

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