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Shrinkage estimation of mean for complex multivariate normal distribution with unknown covariance when p > n

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Virtualconference
Authors : Konno, Yoshihiko (Author of the conference)
CIRM (Publisher )

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Abstract : We consider the problem of estimating the mean vector of the multivariate complex normaldistribution with unknown covariance matrix under an invariant loss function when the samplesize is smaller than the dimension of the mean vector. Following the approach of Chételat and Wells (2012, Ann.Statist, p. 3137–3160), we show that a modification of Baranchik-tpye estimatorsbeats the MLE if it satisfies certain conditions. Based on this result, we propose the James-Stein-like shrinkage and its positive-part estimators.

Keywords : Stein estimator; complex normal distribution; complex Wishart

MSC Codes :
62C20 - Minimax procedures
62F10 - Point estimation
62H12 - Multivariate estimation

Additional resources :
https://www.cirm-math.fr/RepOrga/2146/Slides/Konno.pdf

    Information on the Video

    Film maker : Hennenfent, Guillaume
    Language : English
    Available date : 15/06/2020
    Conference Date : 05/06/2020
    Subseries : Research talks
    arXiv category : Statistics Theory
    Mathematical Area(s) : Probability & Statistics
    Format : MP4 (.mp4) - HD
    Video Time : 00:15:53
    Targeted Audience : Researchers
    Download : https://videos.cirm-math.fr/2020-06-05_Kono.mp4

Information on the Event

Event Title : Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2
Event Organizers : Bogdan, Malgorzata ; Graczyk, Piotr ; Panloup, Fabien ; Proïa, Frédéric ; Roquain, Etienne
Dates : 15/06/2020 - 19/06/2020
Event Year : 2020
Event URL : https://www.cirm-math.com/cirm-virtual-...

Citation Data

DOI : 10.24350/CIRM.V.19641703
Cite this video as: Konno, Yoshihiko (2020). Shrinkage estimation of mean for complex multivariate normal distribution with unknown covariance when p > n. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19641703
URI : http://dx.doi.org/10.24350/CIRM.V.19641703

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