Experimental Investigation of Forecasting Methods Based on Universal Measures

Computer Science – Information Theory

Scientific paper

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Scientific paper

We describe and experimentally investigate a method to construct forecasting
algorithms for stationary and ergodic processes based on universal measures (or
so-called universal data compressors). Using some geophysical and economical
time series as examples, we show that the precision of thus obtained
predictions is higher than that of known methods.

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