Compression-Based Methods for Nonparametric Prediction and Estimation of Some Characteristics of Time Series

Abstract

We address the problem of online prediction for time series. We show that any universal code (or a universal data compressor) can be used as a basis for constructing asymptotically optimal methods for this problem for a certain class of stationary and ergodic processes.