Statistical analysis demonstrates an explicitly computable regression estimator for right-censored data with unknown errors, indicating robust large-sample consistency.
This paper proposes a new estimator of the parameter vector in a linear regression model when the observations are randomly censored on the right and when the error distribution is unknown. This estimator is explicitly defined and easily computable. The paper contains sufficient conditions under which this estimator is mean square consistent and asymptotically normal. A numerical example is given.
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Koul et al. (1981) studied this question.
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