Abstract
The center of symmetry of a distribution function is estimated by a convenient generalized least squares (GLS) estimator, which is constructed from a regression setup based on the strong approximation of the empirical quantile process. This GLS estimator is shown to be semiparametric efficient in the sense of achieving the Fisher information bound. As a by-product, a χ 2 test for the symmetry assumption is also derived.
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.
