Goodness-of-fit tests for censored regression based on artificial data points

Wenceslao González Manteiga (), Cédric Heuchenne (), César Sánchez Sellero () and Alessandro Beretta ()
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Wenceslao González Manteiga: Universidade de Santiago de Compostela
Cédric Heuchenne: HEC Liège, University of Liège
César Sánchez Sellero: Universidade de Santiago de Compostela
Alessandro Beretta: HEC Liège, University of Liège

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 2, No 15, 599-615

Abstract: Abstract Suppose we have a location-scale regression model where the location is the conditional mean and the scale is the conditional standard deviation; the response is possibly right-censored, the covariate is fully observed, and the error is independent of the covariate. We propose new goodness-of-fit testing procedures for the conditional mean and variance based on an integrated regression function technique which uses artificial data points. We obtain the weak convergence of the resulting processes and study their finite sample behavior via simulations. Finally, we analyze a data set about unemployment in Galicia.

Keywords: Bootstrap; Goodness-of-fit tests; Kernel method; Least squares estimation; Nonparametric regression; Right censoring; Survival analysis; 62N03 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11749-019-00662-6

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