Premium
A fully nonparametric diagnostic test for homogeneity of variances
Author(s) -
Wang Lan,
Zhou XiaoHua
Publication year - 2005
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550330406
Subject(s) - nonparametric statistics , homogeneity (statistics) , parametric statistics , mathematics , statistics , variance (accounting) , levene's test , nonparametric regression , f test of equality of variances , analysis of variance , econometrics , statistical hypothesis testing , conditional variance , variance function , regression analysis , test statistic , accounting , business , volatility (finance) , autoregressive conditional heteroskedasticity
The authors propose a new nonparametric diagnostic test for checking the constancy of the conditional variance function σ 2 ( x ) in the regression model Y i = m ( x i ) + σ( x i )ϵ i , i = 1,…, m . Their test, which does not assume a known parametric form for the conditional mean function m ( x ), is inspired by a recent asymptotic theory in the analysis of variance when the number of factor levels is large. The authors demonstrate through simulations the good finite‐sample properties of the test and illustrate its use in a study on the effect of drug utilization on health care costs.