Cross-validation criteria for covariance structures
作者:
Jan G. De Gooijer,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1995)
卷期:
Volume 24,
issue 1
页码: 1-16
ISSN:0361-0918
年代: 1995
DOI:10.1080/03610919508813226
出版商: Marcel Dekker, Inc.
关键词: Factor analysis;Model-selection criteria
数据来源: Taylor
摘要:
A central issue in the analysis of covariance structures is the choice of a suitable model. In this paper two cross-validationCVcriteria are presented for this purpose. For one of these criteria an asymptotically valid approximation is derived. This criterion can be used in conjunction with any correctly specified discrepancy function and is, in comparison with existingCVcriteria, computationally less demanding. The performance of the proposed criterion is evaluated in a Monte Carlo study and compared to the results obtained from various other model-selection criteria, both in small- and large sample situations. An empirical example is given to illustrate its utility in practice. The results demonstrate the effectiveness of the proposedCVcriterion for routinely assessing covariance structural models.
点击下载:
PDF (465KB)
返 回