应用数学2009，Vol.22Issue(2)：297-302,6.
缺失数据下含几何分布的对数线性模型的EM算法
The EM Algorithm in Logistic Linear Models with Geometric Distribution Involving Missing Data
摘要
Abstract
In this paper,a geometric response and normal covariace model for the missing data are assumed.We fit the model using the Monte Carlo EM(Expectation and Maximization) algorithm.The E-step is derived by Metropolis-Hastings algorithm to generate a sample for missing data,and the M-Step is done by Newton-Raphson to maximize the likelihood function.Asymptotic variances and the standard errors of the MLE of parameters are derived using the observed Fisher information.关键词
条件期望/极大似然估计/EM算法/Metropolis-Hastings算法/Newton-Raphson迭代Key words
Conditional expectation/Maximum likelihood estimation/EM algorithm/Metropolis-Hastings algorithm/Newton-Raphson iteration分类
数理科学引用本文复制引用
王继霞,刘次华..缺失数据下含几何分布的对数线性模型的EM算法[J].应用数学,2009,22(2):297-302,6.基金项目
Supported by the National Science Foundation of China(10671057) （10671057）
