Spike-and-Slab Dirichlet Process Mixture Models

• 作者: Kai Cui Wenshan Cui
• 来源期刊: 统计学期刊(英文)
• 学科: 工学
• 关键词: SPIKE and SLAB DIRICHLET Process BAYESIAN EXPECTATION-MAXIMIZATION (BEM) Mixture
• 年，卷（期）: 2012,（5）
• 页码范围: 512-518
• 页数: 7页
• 分类号: TP39

摘要

In this paper, Spike-and-Slab Dirichlet Process (SS-DP) priors are introduced and discussed for non-parametric Bayesian modeling and inference, especially in the mixture models context. Specifying a spike-and-slab base measure for DP priors combines the merits of Dirichlet process and spike-and-slab priors and serves as a flexible approach in Bayesian model selection and averaging. Computationally, Bayesian Expectation-Maximization (BEM) is utilized to obtain MAP estimates. Two simulated examples in mixture modeling and time series analysis contexts demonstrate the models and computational methodology.