Abstract
Linear minimax estimation in linear models with partial parameter restrictions can be reduced to a minimax estimation problem under full parameter restrictions. This is due to the duality between minimax and Bayes estimation w.r.t. least favourable prior distributions, and to a decomposition result for Bayes estimators. As an application we find some new results for minimax estimators under partial parameter restrictions.
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.
