Application of Kolmogorov complexity and universal codes to identity testing and nonparametric testing of serial independence fo

We show that Kolmogorov complexity and such its estimators as universal codes (or data compression methods) can be applied for hypothesis testing in a framework of classical mathematical statistics. The methods for identity testing and nonparametric testing of serial independence for time series are suggested. AMS subject classification: 60G10, 62M07, 68Q30, 68W01, 94A29. Keywords. algorithmic complexity, algorithmic information theory, Kolmogorov complexity, universal coding, hypothesis testing, theory of computation, computational complexity.

• Type: Conference
• Year: 2006
• Where: DAGSTUHL
• Authors: Boris Ryabko, Jaakko Astola, Alexander Gammerman
• Keywords: DAGSTUHL 2006, DAGSTUHL 2007, Data Compression Methods, Hypothesis Testing, Kolmogorov Complexity