Abstract
Abstract We study the problem of how to estimate the parameters of a multivariate hypergeometric distribution when the sample size n is assumed to be an ancillary statistic. The minimax estimator for squared error loss is given. This estimator differs from the well-known minimax estimator for fixed n. Furthermore, that classical estimator is shown to be not even admissible when n is random.
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.
