主题:A novel approach of empirical likelihood with massive data
主讲人:陈夏 陕西师范大学
主持人:姜云卢 BETVLCTOR伟德官网下载
时间:2023年6月16日(周五)上午9:30-10:30
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摘要
In this work, we propose a novel approach to address the challenges posed by empirical likelihood with massive data, which is called split sample mean empirical likelihood (SSMEL), and provides a unique perspective for solving big data problem. We show that the SSMEL preserves the statistical properties of the original empirical likelihood, and thus can be used for statistical inference. It is worth noting that our method does not involve parallel computation, making it applicable to a broad range of computing devices and more feasible for real-world applications. The effectiveness of the proposed method is illustrated by some simulations and real data analysis.
主讲人简介
陈夏,陕西师范大学数学与统计学院副院长、教授、博士生导师。武汉大学概率论与数理统计专业博士,北京师范大学统计学博士后。兼任陕西省统计学学会副理事长和中国现场统计研究会多个分会的常务理事或理事。主要从事高维数据统计分析和概率极限理论方面的研究。在国内外统计学专业学术期刊发表论文30余篇,主持国家自然科学基金重点项目子课题、国家自然科学基金、教育部人文社科基金和陕西省自然科学基金等项目6项,在科学出版社出版专著1部、教材1部,获陕西省高等教育优秀教材一等奖1项、陕西高校科学技术奖二等奖1项。
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校对|王国长
编辑|麦嘉杰
初审|黄振
终审发布|郑贤
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