Mean–field variational approximate Bayesian inference for latent variables models

Guido Consonni, Jean-Michel Marin

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

25 Citazioni (Scopus)

Abstract

The ill-posed nature of missing variable models offers a challenging testing ground for new computational techniques. This is the case for the mean-field variational Bayesian inference. The behavior of this approach in the setting of the Bayesian probit model is illustrated. It is shown that the mean-field variational method always underestimates the posterior variance and, that, for small sample sizes, the mean-field variational approximation to the posterior location could be poor.
Lingua originaleEnglish
pagine (da-a)790-798
Numero di pagine9
RivistaCOMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume52
DOI
Stato di pubblicazionePubblicato - 2007

Keywords

  • Latent variable model
  • Mean-field variational method

Fingerprint Entra nei temi di ricerca di 'Mean–field variational approximate Bayesian inference for latent variables models'. Insieme formano una fingerprint unica.

Cita questo