Nonparametric model checks in censored regression

W. Stute, W. González Manteiga and C. Sánchez Sellero

Communications in Statistics - Theory and Methods, 2000, vol. 29, issue 7, 1611-1629

Abstract: Let M be a parametric model for an unknown regression function m. In order to check the validity of M, i.e., to test for m ∈ M, it is known that optinal tests should be based on the empirical process of the regressors marked by the residuals. In this paper we extend the methodology to censored regression. The asymptotic distribution of the underlying marked empirical process in provided. The Wild Bootstrap, appropriately modified to account for censhorship, provides distributional approximations. The method is applied to simulated data sets as well as tto the Stanford Heart Transplant Data.

Date: 2000
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DOI: 10.1080/03610920008832568

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