Titlebook: Elliptically Symmetric Distributions in Signal Processing and Machine Learning; Jean-Pierre Delmas,Mohammed Nabil El Korso,Frédéri Book 20

APRON

Background on Real and Complex Elliptically Symmetric Distributions,tions?are provided with their main properties. Finally, the estimation of the symmetry center?and scatter matrix?is briefly discussed through the sample mean?(SM), sample covariance matrix?(SCM) estimate, maximum estimate (ML), .-estimators, and Tyler’s .-estimators. Particular attention will be pai

步兵

Robust Estimation with Missing Values for Elliptical Distributions the proposed algorithms are designed to handle various patterns of missing values. At the end of the chapter, the performances of the proposed procedures are illustrated on simulated datasets with missing values. We share a link to a code repository for fully reproducible experiments.

巧思

Semiparametric Estimation in Elliptical Distributionsinfinite-dimensional nuisance term. In particular, the three building blocks of the semiparametric theory, that?are ., .?and ., will be introduced. By means of these abstract concepts, we define the semiparametric counterpart of the Fisher Information Matrix?(FIM) and the related semiparametric effi

積習(xí)已深

Performance Analysis of Subspace-Based Algorithms in CES Data Modelsnce matrix?(SSCM). The asymptotic distributions?of these estimators are also derived. This enables us to unify the asymptotic distribution?of subspace projectors?adapted to the different models of the data and demonstrate various invariance properties that have impacts on the parameters to be estima

小隔間

SEVER

外露

ARCHE

搬運(yùn)工

MORPH