A Comparison Of Robust Regression Techniques For The Estimation Of Weibull Parameters

Douglas R. Shier, Kenneth D. Lawrence

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

In this paper several alternative robust regression techniques are compared for estimating parameters of a Weibull distribution. In addition to the usual least squares (Lj) and least absolute deviation (L) methods, a number of one-step reweighting schemes based on the Lj residuals are considered. The results of an extensive series of Monte Carlo simulation experiments demonstrate that the Anscombe reweighting scheme generally produces the best Weibull estimates over the range of sample sizes and parameter valyes studied.

Original languageEnglish (US)
Pages (from-to)743-750
Number of pages8
JournalCommunications in Statistics - Simulation and Computation
Volume13
Issue number6
DOIs
StatePublished - Jan 1 1984
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation

Keywords

  • Monte Carlo
  • Weibull distribution
  • iteratively reweighted regression
  • least absolute deviation
  • robust

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