On Sequential Estimation and Prediction for Discrete Time Series
AbstractThe problem of extracting as much information as possible from a sequence of observations of a stationary stochastic process X0,X1,…,Xn has been considered by many authors from different points of view. It has long been known through the work of D. Bailey that no universal estimator for P(Xn+1|X0,X1, ...Xn) can be found which converges to the true estimator almost surely. Despite this result, for restricted classes of processes, or for sequences of estimators along stopping times, universal estimators can be found. We present here a survey of some of the recent work that has been done along these lines.
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Bibliographic InfoPaper provided by The Center for the Study of Rationality, Hebrew University, Jerusalem in its series Discussion Paper Series with number dp464.
Length: 32 pages
Date of creation: Sep 2007
Date of revision:
Nonparametric estimation; Stationary processes;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-11-10 (All new papers)
- NEP-ECM-2007-11-10 (Econometrics)
- NEP-ETS-2007-11-10 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Morvai, Gusztáv & Weiss, Benjamin, 2005. "Limitations on intermittent forecasting," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 285-290, May.
- 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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