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【3月20日】模型选择原理和多模型统计推断

发布日期:2015-03-19点击: 发布人:统数院


主题:模型选择原理和多模型统计推断
主讲人:喻达磊博士
时间:2015年3月20日(周五)9:20
地点:北院卓远楼305
主办单位:统计与数学学院
摘要:
Model selection is essentially important when there are different statistical models at hand. In this talk, we consider two important model selection criteria, i.e. Akaike information criterion (AIC) and Bayesian information criterion (BIC). The derivation of these model selection criteria will be introduced and the underlying principles will be discussed. Then the notion of AIC will be extended into the domain of mixed effects models and some new results will be reported.

主讲人喻达磊简介:
香港城市大学统计学博士,副教授。研究领域为随机效应模型、混合模型和空间计量经济学模型的统计推断。在Stat. Med.、J. Multivariate Anal.、Comput. Stat. Data Ana.等国际统计期刊发表论文多篇,担任过Comput. Stat. Data Ana.和Hydrological Sci. J. 等国际期刊的匿名审稿人。



English version

Bi-weekly Research Seminar Series
Topic Model selection principles and multi-model inference
Speaker


  Dr. Dalei Yu
Associate Professor
Department of Statistics
Yunnan University of Finance and Economics
Date 20 March 2015
Time 9:20 – 11:20 a.m.
Venue 305 Zhuo Yuan Bd.

Abstract:
Model selection is essentially important when there are different statistical models at hand. In this talk, we consider two important model selection criteria, i.e. Akaike information criterion (AIC) and Bayesian information criterion (BIC). The derivation of these model selection criteria will be introduced and the underlying principles will be discussed. Then the notion of AIC will be extended into the domain of mixed effects models and some new results will be reported.

All are welcome!