Uniform hypothesis testing for ergodic time series distributions - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Statistics Année : 2012

Uniform hypothesis testing for ergodic time series distributions

Daniil Ryabko
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Résumé

Given a discrete-valued sample $X_1,\dots,X_n$ we wish to decide whether it was generated by a distribution belonging to a family $H_0$, or it was generated by a distribution belonging to a family $H_1$. In this work we assume that all distributions are stationary ergodic, and do not make any further assumptions (e.g. no independence or mixing rate assumptions). We would like to have a test whose probability of error (both Type I and Type II) is uniformly bounded. More precisely, we require that for each $\epsilon$ there exist a sample size $n$ such that probability of error is upper-bounded by $\epsilon$ for samples longer than $n$. We find some necessary and some sufficient conditions on $H_0$ and $H_1$ under which a consistent test (with this notion of consistency) exists. These conditions are topological, with respect to the topology of distributional distance.
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Dates et versions

inria-00610009 , version 1 (20-07-2011)
inria-00610009 , version 2 (26-12-2014)

Identifiants

Citer

Daniil Ryabko. Uniform hypothesis testing for ergodic time series distributions. Statistics, 2012, ⟨10.1080/02331888.2012.71951⟩. ⟨inria-00610009v1⟩
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