Model combining in factorial data analysis Chen, Lihua Yang, Yuhong
dc.contributor.department Statistics 2018-02-16T21:40:57.000 2020-07-02T06:55:54Z 2020-07-02T06:55:54Z 2002-10-01
dc.description.abstract <p>We study the properties of a model combining method, ARM (adaptive regression by mixing), in the ANOVA framework. We propose model instability measures as a guide to the appropriateness of model combining in applications. We further systematically investigate the relationship between ARM performance and the underlying model structure. We propose an approach to evaluating the importance of factors based on the combined estimates. A theoretical risk bound on the combined estimator is also obtained.</p>
dc.description.comments <p>This preprint was published as Lihua Chen, Panayotis Giannakouros, Yuhong Yang, "Model Combining in Factorial Data Analysis", <em>Journal of Statistical Planning and Inference</em> (2007): 2920-2934, doi: <a href="" target="_blank">10.1016/j.jspi.2006.10.005</a>.</p>
dc.identifier archive/
dc.identifier.articleid 1115
dc.identifier.contextkey 7446474
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/119
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 19:00:48 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords model combining
dc.subject.keywords model selection instability
dc.subject.keywords ANOVA
dc.subject.keywords adaptive regression by mixing
dc.title Model combining in factorial data analysis
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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