On Parameter Estimation for Cusp-type Signals
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
On Parameter Estimation for Cusp-type Signals
Author(s) :
Chernoyarov, Oleg [Auteur]
Moscow Power Engineering Institute [MPEI]
Dachian, Serguei [Auteur]
Moscow Power Engineering Institute [MPEI]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Kutoyants, Yu. [Auteur]
Moscow Power Engineering Institute [MPEI]
Laboratoire Manceau de Mathématiques [LMM]
Moscow Power Engineering Institute [MPEI]
Dachian, Serguei [Auteur]
Moscow Power Engineering Institute [MPEI]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Kutoyants, Yu. [Auteur]
Moscow Power Engineering Institute [MPEI]
Laboratoire Manceau de Mathématiques [LMM]
Journal title :
Annals of the Institute of Statistical Mathematics
Pages :
39-62
Publisher :
Springer Verlag
Publication date :
2018
ISSN :
0020-3157
HAL domain(s) :
Statistiques [stat]/Théorie [stat.TH]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Popular science :
Non
Comment :
22 pages
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