In this paper, we study the inference problem in Aalen’s nonparametric additive censored regression models. In particular, we construct a hypothesis test for testing restrictions on regression coefficients, and we propose preliminary test estimators for the target vector parameter. Under the quadratic loss criterion, we also derive the integrated asymptotic distributional risk for the proposed estimators and present an analytic comparison of the preliminary test estimators and the unrestricted benchmark estimator.

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Estimating and Pretesting in Additive Censored Models

  • Sévérien Nkurunziza

摘要

In this paper, we study the inference problem in Aalen’s nonparametric additive censored regression models. In particular, we construct a hypothesis test for testing restrictions on regression coefficients, and we propose preliminary test estimators for the target vector parameter. Under the quadratic loss criterion, we also derive the integrated asymptotic distributional risk for the proposed estimators and present an analytic comparison of the preliminary test estimators and the unrestricted benchmark estimator.