Maximum Likelihood Normal Regression with Censored and Uncensored Data

Abstract

A normal regression situation is considered in which we have data for n+m individuals. The values denote by y_n+1 , y_n+2,…,y_n+m represent right- censored observations. Maximum likelihood estimation of the regression coefficients and residual variance for the normal case with censored and uncensored data is derived and assessed through simulation studies.