PL EN


2016 | 26 | 3 | 57-68
Article title

Advances in antithetic time series analysis: separating fact from artifact

Authors
Content
Title variants
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.
Year
Volume
26
Issue
3
Pages
57-68
Physical description
Contributors
author
  • SBI, Florida A&M University and Department of Scientific Computing, Florida State University, Tallahassee, Fl., USA, dridley@fsu.edu
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-03a469e3-9e3b-47d4-99a4-46ec815361d7
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