Advances in antithetic time series analysis: separating fact from artifact

Journal Title: Operations Research and Decisions - Year 2016, Vol 26, Issue 3

Abstract

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.

Authors and Affiliations

Dennis RIDLEY

Keywords

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  • EP ID EP323622
  • DOI -
  • Views 60
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How To Cite

Dennis RIDLEY (2016). Advances in antithetic time series analysis: separating fact from artifact. Operations Research and Decisions, 26(3), 57-68. https://europub.co.uk/articles/-A-323622