An empirical quantile function for linear models with iid errors

Gilbert Bassett, Roger Koenker

Research output: Contribution to journalArticlepeer-review

Abstract

The regression quantile statistics of Koenker and Bassett (1978) are employed to construct an estimate of the error quantile function in linear models with iid errors. Some finite sample properties and the asymptotic behavior of the proposed estimator are derived. Comparisons with procedures based on residuals are made. The stackloss data of Brownlee (1965) is reanalyzed to illustrate the technique.

Original languageEnglish (US)
Pages (from-to)407-415
Number of pages9
JournalJournal of the American Statistical Association
Volume77
Issue number378
DOIs
StatePublished - Jun 1982

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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