学术报告
【学术报告】Statistical inference on partially validated data and applications
编辑:魏佳发布时间:2021年07月14日

报告人:邱世芳(重庆理工大学)

时  间:723日上午10:30

地  点:厦大海韵园数理大楼6686会议室

内容摘要:

Double sampling is usually applied to collect necessary information for situations in which an infallible classifier is available for validating a subset of the sample that has already been classified by a fallible classifier. Inference procedures are developed based on the partially validated data obtained by the double-sampling process. However, it could happen in practice that such infallible classifier or gold standard does not exist. Hence, we also consider the statistical inference for the case in which both classifiers are fallible under two models, distinguished by the assumption regarding ascertainment of two classifiers. Simulation studies are conducted to evaluate the proposed methods. The applicability of the proposed methods is illustrated by some real examples.

人简介:

邱世芳,女,博士,重庆理工大学教授,硕士生导师;20111月毕业于云南大学概率论与数理统计专业;重庆市数学学会副理事长;新加坡南洋理工大学、香港中文大学等知名高校的访问学者;发表学术论文30余篇,被SCI收录20余篇;主持2项国家自然科学基金面上项目,多项国家统计局统计科研重点项目等省部级项目。主要研究方向是统计推断、生物医学统计、应用统计等。

 

联系人:王海斌