The scan sampler for time series models

• 成果类型: Article
• 署名作者: De Jong, P
• 署名单位: University of London; London School Economics & Political Science
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/84.4.929
• 发表日期: 1997
• 页码: 929937
• 关键词: gaussian state-space; monte-carlo; regression

摘要

An algorithm, called the scan sampler, is developed and discussed. The scan sampler has a variety of uses for time series analysis based on the state space model with non-Gaussian observations. The algorithm is based on the Kalman filter/smoothing algorithm. It can be used for Bayesian inference using Markov chain Monte Carlo and to find posterior modes.