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Local Statistical Modeling via Cluster-Weighted Approach with Elliptical Distributions

Salvatore Ingrassia (), Simona Caterina Minotti () and Giorgio Vittadini ()
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Simona Caterina Minotti: Dipartimento di Statistica, Università degli Studi di Milano-Bicocca

No 20111001, Working Papers from Università degli Studi di Milano-Bicocca, Dipartimento di Statistica

Abstract: Cluster Weighted Modeling (CWM) is a mixture approach regarding the modelisation of the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both the theoretical and numerical point of view; in particular, we show that CWM includes as special cases mixtures of distributions and mixtures of regressions. Further, we introduce CWM based on Student-t distributions providing more robust fitting for groups of observations with longer than normal tails or atypical observations. Theoretical results are illustrated using some empirical studies, considering both real and simulated data.

Keywords: Cluster-Weighted Modeling; Mixture Models; Model-Based Clustering (search for similar items in EconPapers)
Pages: 30 pages
Date: 2011-05-28
New Economics Papers: this item is included in nep-ecm and nep-ure
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Downloads: (external link) Third version, 2011 (application/pdf)
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Journal Article: Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions (2012) Downloads
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