A Simple Randomized Algorithm for Consistent Sequential Prediction of Ergodic Time Series

We 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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Year of publication:	1998
Authors:	Gyorfi, Laszlo ; Lugosi, Gábor ; Morvai, Gusztáv
Publisher:	[S.l.] : SSRN
Subject:	Theorie \| Theory \| Zeitreihenanalyse \| Time series analysis \| Prognoseverfahren \| Forecasting model
Description of contents:	Abstract [papers.ssrn.com]

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Extent:	1 Online-Ressource
Type of publication:	Book / Working Paper
Language:	English
Notes:	Volltext nicht verfügbar
Classification:	C13 - Estimation
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014059754