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Goodness-of-fit tests for parametric models in censored regression
Authors:Juan Carlos Pardo-Fernández  Ingrid Van Keilegom  Wenceslao González-Manteiga
Affiliation:1. Departamento de Estatística e IO. Universidade de Vigo ES-36208 Vigo, Pontevedra, Spain;2. Institut de statistique Université catholique de Louvain BE-1348 Louvain-la-Neuve, Belgium;3. Departamento de Estatística e IO. Universidade de Santiago de Compostela ES-15782 Santiago de Compostela, A Coruña, Spain
Abstract:
The authors propose a goodness-of-fit test for parametric regression models when the response variable is right-censored. Their test compares an estimation of the error distribution based on parametric residuals to another estimation relying on nonparametric residuals. They call on a bootstrap mechanism in order to approximate the critical values of tests based on Kolmogorov-Smirnov and Cramér-von Mises type statistics. They also present the results of Monte Carlo simulations and use data from a study about quasars to illustrate their work.
Keywords:Bootstrap  censored data  goodness-of-fit  heteroscedastic regression  nonparametric regression
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