Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Collection Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Organizer(s) Bogdan, Malgorzata ; Graczyk, Piotr ; Panloup, Fabien ; Proïa, Frédéric ; Roquain, Etienne

Date(s) 15/06/2020 - 19/06/2020

linked URL https://www.cirm-math.com/cirm-virtual-event-2146.html

00:00:00 / 00:00:00

18 25

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

By Yoshihiko Konno

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.

Information about the video

Date of recording 05/06/2020
Date of publication 15/06/2020
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.19641703
Cite this video Konno, Yoshihiko (05/06/2020). Shrinkage estimation of mean for complex multivariate normal distribution with unknown covariance when p > n. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19641703
URL https://dx.doi.org/10.24350/CIRM.V.19641703

Domain(s)

Statistics Theory

MSC codes

Document(s)

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

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