Semiparametric linear regression with censored data and stochastic regressors

Juan Mora

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: We propose three new estimation procedures in the linear regression model with randomly-right censored data when the distribution function of the error term is unspecified, regressors are stochastic and the distribution function of the censoring variable is not necessarily the same for all observations ("unequal censoring"). The proposed procedures are derived combining techniques which produce accurate estimates with "equal censoring" with kernel-conditionalı Kaplan-Meier estimates. The performance of six estimation procedures (the three proposed methods and three alternative ones) is compared by means of some Monte Carlo experiments.

Keywords: Kernel; estimator; Censoring; Linear; regression; Kaplan-Meier; estimator (search for similar items in EconPapers)
Date: 1994-09
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:3954

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