Aligned rank tests for the linear model with heteroscedastic errors

Michael G. Akritas, Willem Albers

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n 1 2 -consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned rank tests to the heteroscedastic linear model. A real data set is used to illustrate the procedure.

Original languageEnglish (US)
Pages (from-to)23-41
Number of pages19
JournalJournal of Statistical Planning and Inference
Volume37
Issue number1
DOIs
StatePublished - Oct 1993

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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