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Register a new userNonparametric Statistical Inference for Ergodic Processes
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Added by
Daniil Ryabko
Publication date
2012
fields
Informatics Engineering
and research's language is
English
Authors
Daniil Ryabko
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In this work a method for statistical analysis of time series is proposed, which is used to obtain solutions to some classical problems of mathematical statistics under the only assumption that the process generating the data is stationary ergodic. Namely, three problems are considered: goodness-of-fit (or identity) testing, process classification, and the change point problem. For each of the problems a test is constructed that is asymptotically accurate for the case when the data is generated by stationary ergodic processes. The tests are based on empirical estimates of distributional distance.
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