Using bootstrap methods to obtain nonnormality robust Chow prediction tests

Autor:	Chris D. Orme, Leslie G. Godfrey
Rok vydání:	2002
Předmět:	Statistics::Theory Economics and Econometrics Statistics Regression analysis Sensitivity (control systems) Predictive failure analysis Chow test Finance Mathematics
Zdroj:	Economics Letters. 76:429-436
ISSN:	0165-1765
DOI:	10.1016/s0165-1765(02)00088-5
Popis:	This paper emphasizes the sensitivity to nonnormality of the standard Chow test for predictive failure. Based on well established asymptotic arguments, a simple double bootstrap procedure is proposed, evaluated and found to be robust to nonnormality.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9462b3fba1aaf0a1f5d70fa8816b6828 https://doi.org/10.1016/s0165-1765(02)00088-5 Zobrazit plný text záznamu Full Text from ScienceDirect