On Parameter Estimation for Cusp-type Signals
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
On Parameter Estimation for Cusp-type Signals
Auteur(s) :
Chernoyarov, Oleg [Auteur]
Moscow Power Engineering Institute [MPEI]
Dachian, Serguei [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Moscow Power Engineering Institute [MPEI]
Kutoyants, Yu. [Auteur]
Laboratoire Manceau de Mathématiques [LMM]
Moscow Power Engineering Institute [MPEI]
Moscow Power Engineering Institute [MPEI]
Dachian, Serguei [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Moscow Power Engineering Institute [MPEI]
Kutoyants, Yu. [Auteur]
Laboratoire Manceau de Mathématiques [LMM]
Moscow Power Engineering Institute [MPEI]
Titre de la revue :
Annals of the Institute of Statistical Mathematics
Pagination :
39-62
Éditeur :
Springer Verlag
Date de publication :
2018
ISSN :
0020-3157
Discipline(s) HAL :
Statistiques [stat]/Théorie [stat.TH]
Résumé en anglais : [en]
We consider the problem of parameter estimation by the observations of deterministic signal in white gaussian noise. It is supposed that the signal has a singularity of cusp-type. The properties of the maximum likelihood ...
Lire la suite >We consider the problem of parameter estimation by the observations of deterministic signal in white gaussian noise. It is supposed that the signal has a singularity of cusp-type. The properties of the maximum likelihood and bayesian estimators are described in the asymptotics of small noise. Special attention is paid to the problem of parameter estimation in the situation of misspecification in regularity, i.e.; the statistician supposes that the observed signal has this singularity, but the real signal is smooth. The rate and the asymptotic distribution of the maximum likelihood estimator in this situation are described.Lire moins >
Lire la suite >We consider the problem of parameter estimation by the observations of deterministic signal in white gaussian noise. It is supposed that the signal has a singularity of cusp-type. The properties of the maximum likelihood and bayesian estimators are described in the asymptotics of small noise. Special attention is paid to the problem of parameter estimation in the situation of misspecification in regularity, i.e.; the statistician supposes that the observed signal has this singularity, but the real signal is smooth. The rate and the asymptotic distribution of the maximum likelihood estimator in this situation are described.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Commentaire :
22 pages
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Source :
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