Robust Estimation with Censored and Grouped Data: An Application of the Em Algorithm

摘要

The adaptation of weighted least squares estimation so that robust estimates can be found with censored or grouped data is discussed. The EM algorithm is implemented for the linear model where the errors are assumed to be generated by a scale mixture of normal distributions. Explicit results are given for the case where the marginal distribution of the error is student-t with an even number of degrees of freedom. Expressions for the observed information are found, relating grouped data results to those for right censored data. Ad-hoc rules for the identification of outliers are given. An example involving the lifetimes of motorettes is considered.