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

Manteiga, Wenceslao González;Heuchenne, Cédric;Sellero, César Sánchez;Beretta, Alessandro
(2020) Test — Vol. 29, p. 599-615 (2020)

Files

ISBARP_2019_36_heuchenne_Goodness-of-fittestsforcensoredregressionbasedonartificialdatapoints_oa_dial.pdf
  • Open Access
  • Adobe PDF
  • 848.21 KB
Download

Details

Authors
  • Manteiga, Wenceslao González
    Author
  • Heuchenne, Cédricorcid-logoUCLouvain
    Author
  • Sellero, César Sánchez
    Author
  • Beretta, Alessandro
    Author
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.
Affiliations

Citations

  • APA
  • Chicago
  • FWB

Manteiga, W. G., Heuchenne, C., Sellero, C. S., & Beretta, A. (2020). Goodness-of-fit tests for censored regression based on artificial data points. Test, 29, 599-615. https://doi.org/10.1007/s11749-019-00662-6 (Original work published 2020)