Abstract
Nonparametric regression is of primary importance in many statistical applications. For the data with censored outcomes, how to construct a confidence band for a regression function is a basic issue but has limited research. We propose a procedure to construct the pointwise and simultaneous confidence bands for a regression function based on a debiased estimator, which is proposed by correcting the bias of the original kernel regression estimator. The corresponding theoretical properties such as consistency, convergence rates, and the asymptotic distribution of the proposed estimator are also derived. Furthermore, we carry out extensive simulation studies and a real data example from the German Breast Cancer study to evaluate the finite sample performance of the proposed method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
