DocumentCode :
2029897
Title :
On Sequence Prediction for Arbitrary Measures
Author :
Ryabko, D. ; Hutter, M.
Author_Institution :
IDSIA, Manno-Lugano
fYear :
2007
fDate :
24-29 June 2007
Firstpage :
2346
Lastpage :
2350
Abstract :
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequences. Consider the question when one of the measures predicts the other, that is, when conditional probabilities converge (in a certain sense), if one of the measures is chosen to generate the sequence. This question may be considered a refinement of the problem of sequence prediction in its most general formulation: for a given class of probability measures, does there exist a measure which predicts all of the measures in the class? To address this problem, we find some conditions on local absolute continuity which are sufficient for prediction and generalize several different notions that are known to be sufficient for prediction. We also formulate some open questions to outline a direction for finding the conditions on classes of measures for which prediction is possible.
Keywords :
probability; sequences; set theory; conditional probability measure; one-way infinite finite-alphabet sequence; sequence prediction problem; set theory; Australia; Bayesian methods; Convergence; Data compression; Economic forecasting; Source coding; Stock markets; Sun; Time measurement; Weather forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 2007. ISIT 2007. IEEE International Symposium on
Conference_Location :
Nice
Print_ISBN :
978-1-4244-1397-3
Type :
conf
DOI :
10.1109/ISIT.2007.4557570
Filename :
4557570
Link To Document :
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