computeELBO: Compute a lower bound on the log-likelihood (ELBO)

In mixedMem: Tools for Discrete Multivariate Mixed Membership Models

Description

computeELBO computes the variational lower bound on the log-likelihood, also called the ELBO, for a mixed membership model.

Usage

computeELBO(model)

Arguments

model

a mixedMemModel object created by the mixedMemModel constructor.

Details

The lower bound (ELBO) is the objective function in the variational EM algorithim. It is a function of the latent variables (φ and δ) and the parameters (α and θ) that be derived from Jensen's inequality:

E_Q{\log[p(X,Z, Λ)]} - E_Q{\log[Q(Z, Λ|φ, δ)]} ≤\log P(obs |α, θ)

Value

computeELBO returns the lower bound on the log-likelihood, a real number.

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