Non-parametric estimation of the residual distribution

Michael G. Akritas, Ingrid Van Keilegom

Research output: Contribution to journalArticlepeer-review

124 Scopus citations

Abstract

Consider a heteroscedastic regression model Y = m(X) + σ(X)ε, where the functions m and σ are "smooth", and ε is independent of X. An estimator of the distribution of ε based on non-parametric regression residuals is proposed and its weak convergence is obtained. Applications to prediction intervals and goodness-of-fit tests are discussed.

Original languageEnglish (US)
Pages (from-to)549-567
Number of pages19
JournalScandinavian Journal of Statistics
Volume28
Issue number3
DOIs
StatePublished - Sep 2001

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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