The global minimum variance unbiased estimator of the parameter for a truncated parameter family under the optimal ranked set sampling

报告人：陈望学

报告地点：数学与统计学院四楼报告厅

报告时间：2019年06月21日星期五14:00-15:00

邀请人：

报告摘要：

The minimum variance unbiased estimators (MVUEs) of the parameters for various distributions are extensively studied under ranked set sampling (RSS). However, the results in existing literatures are only locally MVUEs, i.e. the MVUE in a class of some unbiased estimators is obtained. In this paper, the global MVUE of the parameter in a truncated parameter family is obtained, that is to say, it is the MVUE in the class of all unbiased estimators. Firstly we find the optimal RSS according to the character of a truncated parameter family, i.e. arrange RSS based on complete and sufficient statistics of independent and identically distributed samples. Then under this RSS, the global MVUE of the parameter in a truncated parameter family is found. Numerical simulations for some usual distributions inthis family fully support the result from the above two-step optimizations. A real data set is used for illustration.

主讲人简介：

男，副教授，1984年出生，汉族，甘肃陇南人，统计学博士，中共党员。2009年6月在吉首大学获理学学士学位，2012年6月毕业于华中师范大学概率统计专业，获统计学硕士学位，2016年6月毕业于华中师范大学数学与统计学学院，获统计学博士学位。主要研究领域：抽样设计与数据分析。