1. Goodness-of-fit tests for censored regression based on artificial data points
- Author
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Wenceslao González Manteiga, Cédric Heuchenne, César Sánchez Sellero, Alessandro Beretta, and UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
- Subjects
Least squares estimation ,Statistics and Probability ,Conditional expectation ,01 natural sciences ,Standard deviation ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Goodness of fit ,Covariate ,Statistics ,Econometrics ,0101 mathematics ,Mathematics ,Right censoring ,Censored regression model ,Goodness-of-fit tests ,Weak convergence ,Regression analysis ,Nonparametric regression ,Survival analysis ,Bootstrap ,Kernel method ,030211 gastroenterology & hepatology ,Statistics, Probability and Uncertainty - 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.
- Published
- 2019