Year: 2008
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Ryabko, Daniil, Ryabko, Boris
Institution: Centre Inria de l'Université de Lille
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Award: G1391404679
OpenAlex ID: W2952939740