Modelling structured correlation matrices
成果类型：
Article
署名作者：
Tsay, Ruey S.; Pourahmadi, Mohsen
署名单位：
University of Chicago; Texas A&M University System; Texas A&M University College Station
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asw061
发表日期：
2017
页码：
237242
关键词：
摘要：
Ensuring positive definiteness of an estimated structured correlation matrix is challenging. We show that reparameterizing Cholesky factors of correlation matrices using hyperspherical coordinates or angles provides a flexible and effective solution. Once a structured correlation matrix is identified, the corresponding angles and hence the constrained correlations may be estimated by maximum likelihood. Consistency and asymptotic normality of the maximum likelihood estimators of the angles are established. Examples demonstrate the flexibility of the method.
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