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Strategies for sequential prediction of stationary time series (2000).
| Content Provider | CiteSeerX |
|---|---|
| Author | Györfi, László Lugosi, Gábor |
| Abstract | We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combination of several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes. |
| File Format | |
| Publisher Date | 2000-01-01 |
| Access Restriction | Open |
| Subject Keyword | Sequential Prediction Stationary Time Series Analog Result Ergodic Random Process Bayes Predictor Squared Error Converges Several Simple Predictor Bounded Stationary Stationary Gaussian Process Simple Procedure |
| Content Type | Text |
