A principal subspace theorem for 2-principal points of general location mixtures of spherically symmetric distributions

DOI10.1016/j.spl.2010.08.012zbMath1202.62070OpenAlexW2039588635MaRDI QIDQ613175

Hiroshi Kurata, Shun Matsuura

Publication date: 20 December 2010

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2010.08.012

zbMATH Keywords

principal pointsspherically symmetric distributionlocation mixturemean squared distance

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Approximations to statistical distributions (nonasymptotic) (62E17)

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Properties and generation of representative points of the exponential distribution, Representative points for location-biased datasets, A note on the fourth cumulant of a finite mixture distribution, Principal points of a multivariate mixture distribution, Optimal estimators of principal points for minimizing expected mean squared distance, Optimal principal points estimators of multivariate distributions of location-scale and location-scale-rotation families, Self-consistency and a generalized principal subspace theorem, Principal points for an allometric extension model, High precision numerical computation of principal points for univariate distributions, Three kinds of discrete approximations of statistical multivariate distributions and their applications

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