Exact Gaussian maximum likelihood and simulation for regularly-spaced observations with Gaussian correlations
成果类型：
Article
署名作者：
Martin, RJ
署名单位：
University of Sheffield
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/87.3.727
发表日期：
2000
页码：
727730
关键词：
摘要：
For regularly-spaced observations with the Gaussian autocorrelation function, the finite and infinite autoregressive and moving-average representations can be obtained theoretically. This allows exact Gaussian maximum likelihood to be performed very accurately, and gives a simple exact simulation method.