Uniform hypothesis testing for finite-valued ...
Type de document :
Article dans une revue scientifique: Article original
Titre :
Uniform hypothesis testing for finite-valued stationary processes
Auteur(s) :
Titre de la revue :
Statistics
Pagination :
121-128
Éditeur :
Taylor & Francis: STM, Behavioural Science and Public Health Titles
Date de publication :
2014
ISSN :
0233-1888
Mot(s)-clé(s) en anglais :
property testing
stationary processes
ergodic time series
hypothesis testing
stationary processes
ergodic time series
hypothesis testing
Discipline(s) HAL :
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Informatique [cs]/Théorie de l'information [cs.IT]
Mathématiques [math]/Théorie de l'information et codage [math.IT]
Statistiques [stat]/Théorie [stat.TH]
Informatique [cs]/Théorie de l'information [cs.IT]
Mathématiques [math]/Théorie de l'information et codage [math.IT]
Résumé en anglais : [en]
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 ...
Lire la suite >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.Lire moins >
Lire la suite >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.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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- http://arxiv.org/pdf/1107.4165
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- 1107.4165
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