Local Statistical Modeling via Cluster-Weighted Approach with Elliptical Distributions
AbstractCluster 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.
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Bibliographic InfoPaper provided by Università degli Studi di Milano-Bicocca, Dipartimento di Statistica in its series Working Papers with number 20111001.
Length: 30 pages
Date of creation: 28 May 2011
Date of revision:
Cluster-Weighted Modeling; Mixture Models; Model-Based Clustering;
Other versions of this item:
- Salvatore Ingrassia & Simona Minotti & Giorgio Vittadini, 2012. "Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions," Journal of Classification, Springer, vol. 29(3), pages 363-401, October.
- NEP-ALL-2011-11-01 (All new papers)
- NEP-ECM-2011-11-01 (Econometrics)
- NEP-URE-2011-11-01 (Urban & Real Estate Economics)
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