THE IMPACT OF EXTREME OBSERVATIONS ON SIMPLE FORECASTING METHODS

Orsay Kucukemiroglu, Keith Ord

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

In general linear modeling, an alternative to the method of least squares (LS) is the least absolute deviations (LAD) procedure. Although LS is more widely used, the LAD approach yields better estimates in the presence of outliers. In this paper, we examine the performance of LAD estimators for the parameters of the first‐order autoregressive model in the presence of outliers. A simulation study compared these estimates with those given by LS. The general conclusion is that LAD does not deal successfully with additive outliers. A simple procedure is proposed which allows exception reporting when outliers occur.

Original languageEnglish (US)
Pages (from-to)299-308
Number of pages10
JournalDecision Sciences
Volume16
Issue number3
DOIs
Publication statusPublished - Jul 1985

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All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

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