Advances in antithetic time series analysis: separating fact from artifact

• Autorzy: Ridley D.

Identyfikatory

DOI

10.5277/ord160304

• Języki publikacji: EN

Abstrakty

EN

The problem of biased time series mathematical model parameter estimates is well known to be insurmountable. When used to predict future values by extrapolation, even a de minimis bias will eventually grow into a large bias, with misleading results. This paper elucidates how combining antithetic time series solves this baffling problem of bias in the fitted and forecast values by dynamic bias cancellation. Instead of growing to infinity, the average error can converge to a constant.

Słowa kluczowe

EN

combining; antithetic; time series; bias correction; serial correlation

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2016
• Tom: Vol. 26, No. 3
• Strony: 57--68
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Ridley D.

• SBI, Florida A&M University and Department of Scientific Computing, Florida State University, Tallahassee, Fl., USA

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.