Strategies for sequential prediction of stationary time series
| Contribuinte(s) |
Universitat Pompeu Fabra. Departament d'Economia i Empresa |
|---|---|
| Data(s) |
15/09/2005
|
| Resumo |
We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof 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. |
| Identificador | |
| Idioma(s) |
eng |
| Direitos |
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons info:eu-repo/semantics/openAccess <a href="http://creativecommons.org/licenses/by-nc-nd/3.0/es/">http://creativecommons.org/licenses/by-nc-nd/3.0/es/</a> |
| Palavras-Chave | #Statistics, Econometrics and Quantitative Methods #sequential prediction #ergodic process #individual sequence #gaussian process |
| Tipo |
info:eu-repo/semantics/workingPaper |
