Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients

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.