Nonnested model comparisons for time series

• 成果类型: Article
• 署名作者: Mcelroy, T. S.
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asw048
• 发表日期: 2016
• 页码: 905914
• 关键词: equal forecast accuracy; predictive ability; tests; hypotheses; inference; selection

摘要

This paper addresses the topic of nonnested time series model comparisons. The main result is a central limit theorem for the likelihood ratio statistic when the models are nonnested and non-equivalent. The concepts of model equivalence and forecast equivalence, which are important for determining the parameter subset corresponding to the null hypothesis, are developed. The method is validated through a simulation study and illustrated on a retail time series.