Advances in antithetic time series analysis: separating fact from artifact

• Authors: RIDLEY Dennis
• Languages of publication: EN

Abstracts

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 even-tually 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 can-cellation. Instead of growing to infinity, the average error can converge to a constant.

Keywords

EN

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

• Publisher: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
• Journal: Operations Research and Decisions
• Year: 2016
• Volume: 26
• Issue: 3
• Pages: 57-68

Contributors

author

RIDLEY Dennis

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

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Identifiers

DOI

10.5277/ord160304