Goodness-of-fit tests for parametric models in censored regression |
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Authors: | Juan Carlos Pardo-Fernández Ingrid Van Keilegom Wenceslao González-Manteiga |
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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 |
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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. |
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Keywords: | Bootstrap censored data goodness-of-fit heteroscedastic regression nonparametric regression |
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