A hybrid EM/Gauss-Newton algorithm for maximum likelihood in mixture distributions

Statistics and Computing

Volumn 6, Issue 2, 1996, Pages 127-130

  Aitkin, Murray ^a,b   Aitkin, Irit ^c  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

^c CURTIN UNIVERSITY   (Australia)

Author keywords

EM algorithm; Gauss Newton; Maximum likelihood; Mixtures

Indexed keywords

EID: 21344464829     PISSN: 09603174     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF00162523     Document Type: Article

References (9)

1. Aitkin, M. (1980) Mixture applications of the EM algorithm in GLIM. In COMPSTAT 1980. Physica-Verlag, Vienna.
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3. Everitt, B. S. (1984) Maximum likelihood estimation of the parameters in a mixture of two univariate normal distributions: a comparison of different algorithms. The Statistician, 33, 205-15.
4. Louis, T. A. (1982) Finding the observed information when using the EM algorithm. J. Roy. Statist. Soc. B, 44, 226-33.
5. Meilijson, I. (1989) A fast improvement to the EM algorithm on its own terms. J. Roy. Statist. Soc. B, 51, 127-38.
6. McLachlan, G. J. and Basford, K. (1988) Mixture Models: Inference and Applications to Clustering. Dekker, New York.
7. Meng, X.-L. and Rubin, D. R. (1991) Using EM to obtain asymptotic variance-covariance matrices: the SEM algorithm. J. Amer. Statist. Assoc., 86, 899-909.
8. Redner, R. A. and Walker, H. F. (1984) Mixture densities, maximum likelihood and the EM algorithm. SIAM Review, 26, 195-239.
9. Titterington, D. M., Smith, A. F. M. and Makov, U. E. (1985) Statistical Analysis of Finite Mixture Distributions. Wiley, Chichester.