Tests of linear hypotheses based on regression rank scores

C. Gutenbrunner, J. JurečKová, R. Koenker, S. Portnoy

Research output: Contribution to journalArticle

Abstract

We propose a general class of asymptotically distribution-free tests of a linear hypothesis in the linear regression model. The tests are based on regression rank scores, recentlyintroduced by Gutenbrunner and Jurečková (1992) as dual variables to the regression quantiles of Koenker and Bassett (1978). Their properties are analogous to those of the corresponding rank tests in location model. Unlike the other regression tests based on aligned rank statistics, however, our tests do not require preliminary estimation of nuisance parameters, indeed they are invariant with respect to a regression shift of the nuisance parameters.

Original languageEnglish (US)
Pages (from-to)307-331
Number of pages25
JournalJournal of Nonparametric Statistics
Volume2
Issue number4
DOIs
StatePublished - Jan 1 1993

Keywords

  • Ranks
  • regression quantiles
  • regression rank scores

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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