首页 | 本学科首页   官方微博 | 高级检索  
     


Meta-analysis,pretest, and shrinkage estimation of kurtosis parameters
Authors:Nighat Zahra  Supranee Lisawadi  S. Ejaz Ahmed
Affiliation:1. Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Thailand;2. Department of Mathematics and Statistics, Brock University, St. Catharines, ON, Canada
Abstract:An asymptotic theory for the improved estimation of kurtosis parameter vector is developed for multi-sample case using uncertain prior information (UPI) that several kurtosis parameters are the same. Meta-analysis is performed to obtain pooled estimator, as it is a statistical methodology for pooling quantitative evidence. Pooled estimator is a good choice when assumption of homogeneity holds but it becomes inconsistent as assumption violates, therefore pretest and Stein-type shrinkage estimators are proposed as they combine sample and nonsample information in a superior way. Asymptotic properties of suggested estimators are discussed and their risk comparisons are also mentioned.
Keywords:Asymptotic distributional bias  Asymptotic quadratic risk  Kurtosis  Meta-Analysis  Shrinkage and pretest estimation  Simulation  Uncertain prior information
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号