Nonparametric Estimation of the Conditional Mean Residual Life Function Based on Censored Data
نویسندگان
چکیده
The conditional mean residual life (MRL) function is the expected remaining life given a set of predictors. In this work we consider two nonparametric estimators of the conditional MRL function when the lifetime variable is subject to right censoring. We discuss some theoretical difficulties with current semiparametric models for MRL function estimation methods. We derive the asymptotic consistency of both estimators proposed. The numerical properties of the proposed estimators are investigated via simulation study, and compared to semiparametric estimators in varying settings. We apply the proposed methods to the World Bank’s 1997 cross-section Vietnam Living Standards Survey, to demonstrate the applicability of the MRL function to cost data.
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