Some p-variate adaptations of the shapiro-wilk test of normality

Autor:	C. Thomas Lin, Govind S. Mudholkar, Deo Kumar Srivastava
Rok vydání:	1995
Předmět:	Statistics and Probability Multivariate statistics media_common.quotation_subject Univariate Normality test Shapiro–Wilk test Statistics Econometrics Chi-square test ANOVA on ranks Normality Mathematics Type I and type II errors media_common
Zdroj:	Communications in Statistics - Theory and Methods. 24:953-985
ISSN:	1532-415X 0361-0926
DOI:	10.1080/03610929508831533
Popis:	The assumption of multivariate normality is a common prac-tice in the analyses of multivariate data. But it is rarely verified, in part, because of the lack of simple and easy to use test proce-dures to detect such violations. In this paper we decompose the problem of testing the hypothesis of multivariate normality into component problems of testing univariate normality. These prob-lems are then solved using the well known W-test due to Shapiro and Wilk (1965). The operating characteristics of the new test procedures are evaluated and compared with Z p test due to Mud-holkar, McDermott, and Srivastava (1992) and test due to Mardia and Foster (1983). An extensive simulation study demon strates that the new test procedures have excellent type I error control for samples of size as small as 20 and have superior power properties as compared to their competitors.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8f95fbed3ecd70b5d6d8794e1ab2678e https://doi.org/10.1080/03610929508831533 Zobrazit plný text záznamu