Burmann expansion and test for additivity

• 成果类型: Article
• 署名作者: Chan, KS; Kristoffersen, AB; Stenseth, NC
• 署名单位: University of Iowa; University of Oslo; University of Oslo
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/90.1.209
• 发表日期: 2003
• 页码: 209222
• 关键词: nonlinear time-series; INVARIANCE-PRINCIPLES; regression

摘要

We propose a Lagrange multiplier test for additivity based on the Burmann expansion of a conditional mean function. The asymptotic null distribution of the test is shown to be chi(2), under some regularity conditions. In contrast; the Lagrange multiplier test proposed by Chen et al. (1995) is based on the Volterra expansion of-the conditional mean function. We discuss some desirable advantages of the Burmann expansion over the Volterra expansion for nonlinear time series modelling. We also reported an empirical study which shows that, in terms of empirical power, the Lagrange multiplier-test motivated by the Burmann expansion outperforms the test of Chen et al. (1995) for the cases for which the Lagrange multiplier test is designed. For other cases for which none of the tests is specifically designed, the empirical powers of the two tests are comparable. Finally, we illustrated the use of the Lagrange multiplier test with a blowfly experimental system.