Title :
Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients
Author :
Xingcai Zhou ; Changchun Tan
Author_Institution :
Dept. of Math. & Comput. Sci., Tongling Univ., Tongling, China
Abstract :
Generalized linear models have many applications in agriculture, biology, and so on. With the need of applications, it was extended from various ways for more general cases. The paper proposes an extended finite mixture of generalized linear random effects models (GLMMs) with Varying Coefficients, based on the finite mixture distribution and GLMMs with varying coefficients, then parameters are estimated via Monte Carlo EM (MCEM) algorithm.
Keywords :
Monte Carlo methods; statistical distributions; GLMM; Monte Carlo EM algorithm; finite mixture distribution; generalized linear random effect model; Approximation algorithms; Biological system modeling; Computational modeling; Data models; Educational institutions; Mathematical model; Monte Carlo methods; EM algorithm; Generalized linear models; Monte Carlo; Random effects; Varying coefficients;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6022859
