Boldea, Otilia and Magnus, Jan R. (2009): Maximum Likelihood Estimation of the Multivariate Normal Mixture Model. Published in: Journal of the American Statistical Association , Vol. 104, No. 488 (2009): pp. 15391549.

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Abstract
The Hessian of the multivariate normal mixture model is derived, and estimators of the information matrix are obtained, thus enabling consistent estimation of all parameters and their precisions. The usefulness of the new theory is illustrated with two examples and some simulation experiments. The newly proposed estimators appear to be superior to the existing ones.
Item Type:  MPRA Paper 

Original Title:  Maximum Likelihood Estimation of the Multivariate Normal Mixture Model 
Language:  English 
Keywords:  Mixture model; Maximum likelihood; Information matrix 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C10  General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General 
Item ID:  23149 
Depositing User:  Otilia Boldea 
Date Deposited:  08 Jun 2010 21:47 
Last Modified:  26 Sep 2019 08:13 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/23149 