Hyperspectral parameter estimation of elliptically contoured t mixture models using expectation-maximisation

2005 ◽  
Vol 26 (22) ◽  
pp. 5071-5097 ◽  
Author(s):  
M. D. Farrell ◽  
R. M. Mersereau
Keyword(s):  
Parameter Estimation ◽  
Mixture Models ◽  
Expectation Maximisation ◽  
Elliptically Contoured

scholarly journals Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models

2011 ◽  
Vol 23 (6) ◽  
pp. 1605-1622 ◽  
Author(s):  
Lingyan Ruan ◽  
Ming Yuan ◽  
Hui Zou
Keyword(s):  
Parameter Estimation ◽  
Mixture Models ◽  
Gaussian Mixture Models ◽  
Expectation Maximization Algorithm ◽  
Real Data ◽  
Gaussian Mixture ◽  
High Dimensional ◽  
Model Based Clustering ◽  
Text Type ◽  
Effective Dimensionality

Finite gaussian mixture models are widely used in statistics thanks to their great flexibility. However, parameter estimation for gaussian mixture models with high dimensionality can be challenging because of the large number of parameters that need to be estimated. In this letter, we propose a penalized likelihood estimator to address this difficulty. The [Formula: see text]-type penalty we impose on the inverse covariance matrices encourages sparsity on its entries and therefore helps to reduce the effective dimensionality of the problem. We show that the proposed estimate can be efficiently computed using an expectation-maximization algorithm. To illustrate the practical merits of the proposed method, we consider its applications in model-based clustering and mixture discriminant analysis. Numerical experiments with both simulated and real data show that the new method is a valuable tool for high-dimensional data analysis.

scholarly journals PARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELS

2014 ◽  
Vol 10 (10) ◽  
pp. 2124-2134 ◽  
Author(s):  
G. F. Araújo ◽  
H. T. Macedo ◽  
M. T. Chella ◽  
C. A.E. Montesco ◽  
M. V.O. Medeiros
Keyword(s):  
Mixture Models ◽  
Parallel Implementation ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Expectation Maximisation
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