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Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions

Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both theoretical and numerical point of view; in particular, we show that Gaussian CWM includes mixtures of distributions and mixtures of regressions as special cases. Further, we introduce CWM based on Student-t distributions, which provides a more robust fit for groups of observations with longer than normal tails or noise data. Theoretical results are illustrated using some empirical studies, considering both simulated and real data. Some generalizations of such models are also outlined. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Classification Springer Journals

Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions

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References (64)

Publisher
Springer Journals
Copyright
Copyright © 2012 by Springer Science+Business Media, LLC
Subject
Statistics; Marketing; Bioinformatics; Psychometrics; Pattern Recognition; Signal, Image and Speech Processing; Statistical Theory and Methods
ISSN
0176-4268
eISSN
1432-1343
DOI
10.1007/s00357-012-9114-3
Publisher site
See Article on Publisher Site

Abstract

Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both theoretical and numerical point of view; in particular, we show that Gaussian CWM includes mixtures of distributions and mixtures of regressions as special cases. Further, we introduce CWM based on Student-t distributions, which provides a more robust fit for groups of observations with longer than normal tails or noise data. Theoretical results are illustrated using some empirical studies, considering both simulated and real data. Some generalizations of such models are also outlined.

Journal

Journal of ClassificationSpringer Journals

Published: Aug 23, 2012

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