Fast sampling of Gaussian Markov random fields

• 成果类型: Article
• 署名作者: Rue, H
• 署名单位: Norwegian University of Science & Technology (NTNU)
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/1467-9868.00288
• 发表日期: 2001
• 页码: 325-338
• 关键词: blocking

摘要

This paper demonstrates how Gaussian Markov random fields (conditional autoregressions) can be sampled quickly by using numerical techniques for sparse matrices. The algorithm is general and efficient, and expands easily to various forms for conditional simulation and evaluation of normalization constants. We demonstrate its use by constructing efficient block updates in Markov chain Monte Carlo algorithms for disease mapping.