Regression analysis with randomly right censored data

by H. L. Koul, V. Susarla, John Van Ryzin

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Analyzes the asymptotic distribution theory of three sets of estimators for the parameters in the linear regression model when the observations are randomly censored on the right and when the error distribution is unknown. These estimators are shown to be consistent under various assumptions on the censoring distributions. Some comparison of the asymptotic variances of some of the estimators for some error distributions is also given. A numerical example based on real data is given to illustrate the estimators.

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