A new approach of genetic-based EM algorithm for mixture models
暂无分享,去创建一个
[1] R. Sundberg. An iterative method for solution of the likelihood equations for incomplete data from exponential families , 1976 .
[2] P. Green,et al. On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion) , 1997 .
[3] William B. Langdon,et al. Genetic Programming — Computers Using “Natural Selection” to Generate Programs , 1998 .
[4] M. Woodbury. A missing information principle: theory and applications , 1972 .
[5] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[6] William H. Richardson,et al. Bayesian-Based Iterative Method of Image Restoration , 1972 .
[7] M. Healy,et al. Missing Values in Experiments Analysed on Automatic Computers , 1956 .
[8] C. A. Smith,et al. THE ESTIMATION OF GENE FREQUENCIES IN A RANDOM‐MATING POPULATION , 1955, Annals of human genetics.
[9] S. Newcomb. A Generalized Theory of the Combination of Observations so as to Obtain the Best Result , 1886 .
[10] Thomas Bäck,et al. Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .
[11] B. Blight. Estimation from a censored sample for the exponential family , 1970 .
[12] Melanie Mitchell,et al. An introduction to genetic algorithms , 1996 .
[13] Xiao-Li Meng,et al. The EM Algorithm—an Old Folk‐song Sung to a Fast New Tune , 1997 .
[14] Geoffrey J. McLachlan,et al. Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.
[15] Cedric A. B. Smith,et al. COUNTING METHODS IN GENETICAL STATISTICS , 1957 .