Maximum Likelihood Estimation of Parameters inuda Mixture Model

摘要

The estimation of parameters of the log normal distribution based on complete and censored samples are considered in the literature. In this article, the problem of estimatingudthe parameters of log normal mixture model is considered. The Expectation Maximization algorithm is used to obtain maximum likelihood estimators for the parameters, asudthe likelihood equation does not yield closed form expression. The standard errors ofudthe estimates are obtained. The methodology developed here is then illustrated throughudsimulation studies. The confidence interval based on large-sample theory is obtained.