2014/02/25 by Minh‐Ngoc Tran, M. -N. Tran, Tran, M. -N. +9
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #stat.ME
paper · pdf · doi:10.48550/arxiv.1402.6035
27 pages, 2 figures
arxiv created 2014/02/25 · openalex publication_date 2014/02/25 · arxiv updated 2014/02/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper is concerned with Bayesian inference when the likelihood is analytically intractable but can be unbiasedly estimated. We propose an annealed importance sampling procedure for estimating expectations with respect to the posterior. The proposed algorithm is useful in cases where finding a good proposal density is challenging, and when estimates of the marginal likelihood are required. The effect of likelihood estimation is investigated, and the results provide guidelines on how to set up the precision of the likelihood estimation in order to optimally implement the procedure. The methodological results are empirically demonstrated in several simulated and real data examples.