To access the full text documents, please follow this link:

Strategies for sequential prediction of stationary time series;
Modeling Uncertainty:An examination of its theory, methods, and applications (book)
Györfi, László; Lugosi, Gábor
Universitat Pompeu Fabra. Departament d'Economia i Empresa
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.
Statistics, Econometrics and Quantitative Methods
sequential prediction
ergodic process
individual sequence
gaussian process
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
Working Paper

Show full item record