A simple randomized algorithm for consistent sequential prediction of ergodic time series
AbstractWe present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if the sequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.
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Bibliographic InfoPaper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 282.
Date of creation: Apr 1998
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Web page: http://www.econ.upf.edu/
Prediction; ergodic processes; pattern classification;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-1998-09-14 (All new papers)
- NEP-ECM-1998-09-14 (Econometrics)
- NEP-ETS-1998-09-14 (Econometric Time Series)
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- Gusztáv Morvai & Benjamin Weiss, 2004. "Intermittent estimation of stationary time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 13(2), pages 525-542, December.
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