Estimating the parameters of hidden binomial trials by the EM algorithm

Authors : Degang ZHU

Pages : 885-890

View : 15 | Download : 6

Publication Date : 2014-10-01

Article Type : Research Paper

Abstract :The EM algorithm has become a popular efficient iterative procedure to compute the maximum likelihood insert ignore into journalissuearticles values(ML); estimate in the presence of incomplete data. Each iteration of the EM algorithm involves two steps called expectation step insert ignore into journalissuearticles values(E-step); and maximization step insert ignore into journalissuearticles values(M-step);. Complexity of statistical model usually makes the iteration of maximization step difficult. An identity on which the derivation of the EM algorithm is based is presented. It is showed that deriving iteration formula of parameter of hidden binomial trials based on the identity is much simpler than that in common M-step. 
Keywords : Maximum likelihood, EM algorithm, incomplete data, hidden binomial trials, identity