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. 1539-1549.
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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|
|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
|Depositing User:||Otilia Boldea|
|Date Deposited:||08. Jun 2010 21:47|
|Last Modified:||11. Feb 2013 22:13|
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