AN ADAPTIVE APPROACH TO TIME‐SERIES FORECASTING

Stuart Bretschneider, Robert Carbone, Richard L. Longini

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

This paper extends the applicability of the Carbone‐Longini adaptive estimation procedure (AEP) to time‐series forecasting. Comparisons with adaptive filtering, the Box‐Jenkins methodology, and multiple regression analysis as it applies to time‐series analysis are provided. Specific time‐series data examined by Box and Jenkins and Box and Tiao constitute the basis for these comparisons. The analysis of the results indicate the robustness and performance superiority of the simple distributive‐lag forecast model coupled with the concept of adaptively “tracking” rather than “fitting” historical data.

Original languageEnglish (US)
Pages (from-to)232-244
Number of pages13
JournalDecision Sciences
Volume10
Issue number2
DOIs
StatePublished - 1979
Externally publishedYes

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Adaptive filtering
Regression analysis
Time series forecasting
Time series data
Multiple regression analysis
Time series analysis
Methodology
Robustness
Adaptive estimation

ASJC Scopus subject areas

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

Cite this

AN ADAPTIVE APPROACH TO TIME‐SERIES FORECASTING. / Bretschneider, Stuart; Carbone, Robert; Longini, Richard L.

In: Decision Sciences, Vol. 10, No. 2, 1979, p. 232-244.

Research output: Contribution to journalArticle

Bretschneider, Stuart ; Carbone, Robert ; Longini, Richard L. / AN ADAPTIVE APPROACH TO TIME‐SERIES FORECASTING. In: Decision Sciences. 1979 ; Vol. 10, No. 2. pp. 232-244.
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