An ANOVA-type nonparametric diagnostic test for heteroscedastic regression models

Lan Wang, Michael G. Akritas, Ingrid Van Keilegom

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

For the heteroscedastic nonparametric regression model Yni=m (xni)+σ (xnini, i=1,...,n, we discuss a novel method for testing some parametric assumptions about the regression function m. The test is motivated by recent developments in the asymptotic theory for analysis of variance when the number of factor levels is large. Asymptotic normality of the test statistic is established under the null hypothesis and suitable local alternatives. The similarity of the form of the test statistic to that of the classical F-statistic in analysis of variance allows easy and fast calculation. Simulation studies demonstrate that the new test possesses satisfactory finite-sample properties.

Original languageEnglish (US)
Pages (from-to)365-382
Number of pages18
JournalJournal of Nonparametric Statistics
Volume20
Issue number5
DOIs
StatePublished - Jul 2008

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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