Paper #282

Title:

A simple randomized algorithm for consistent sequential prediction of ergodic time series

Authors:

László Györfi, Gábor Lugosi and Gusztáv Morvai

Date:

April 1998

Abstract:

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.

Keywords:

Prediction, ergodic processes, pattern classification

JEL codes:

C13

Area of Research:

Statistics, Econometrics and Quantitative Methods

Published in:

IEEE Transactions on Information Theory, 45, (1999), pp. 2642-2650

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