RT Generic
T1 Semiparametric linear regression with censored data and stochastic regressors
A1 Mora, Juan
A2 Universidad Carlos III de Madrid. Departamento de Estadística, 
AB 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.
YR 1994
FD 1994-09
LK http://hdl.handle.net/10016/3954
UL http://hdl.handle.net/10016/3954
LA eng
DS e-Archivo
RD 27 abr. 2024