Abstract
The kernel method estimator of the spatial modal regression for functional regressors is proposed. We establish, under some general mixing conditions, the $$L^p$$ -consistency and the asymptotic normality of the estimator. The performance of the proposed estimator is illustrated in a real data application.
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.
