Nonparametric statistical inference for ergodic processes

8 years 6 months ago
Nonparametric statistical inference for ergodic processes
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.
Daniil Ryabko, Boris Ryabko
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TIT
Authors Daniil Ryabko, Boris Ryabko
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