﻿ 关于举办“天财统计大讲堂”讲座的通知-彩神大发彩票代理

 学生 | 教职工 | 校友 | 未来学生 | 招聘与访客

 关于举办“天财统计大讲堂”讲座的通知 2019-11-05 08:32 统计学院 题  目：Asymptotic Efficiency of the Pseudo-Maximum Likelihood Estimator in Multi-Group Factor Models 主讲人：杨帆（瑞典乌普萨拉大学） 时  间：2019年11月13日13:30 地  点：二教111 讲座内容：In practice, the presence of different strata is typically unknown; pooling observations from several normal populations is an example. Distribution of pooled data becomes a mixture of normal distributions. In this study, the effect of pooling data is investigated through a two-group factor model. Two independent normal populations are pooled together. A single-group factor model is fitted to the pooled data set using pseudo-maximum likelihood (PML) where the data are treated as normally distributed and the normal theory ML is applied. The asymptotic standard errors of factor loadings for the single-group factor model are computed and compared with the asymptotic standard errors from the multi-group ML approach. Theoretically, the multi-group ML estimators should be asymptotically efficient. However, the results from our numerical study show that the PML is more efficient than the multi-group ML. A mathematical rationale shows that the standard errors from the PML are underestimated. Such underestimation is due to the ignorance of the effects of factor means and covariances in different groups. Therefore, the normal theory ML is not robust for pooled data. Especially, it largely underestimates the variances of factor loadings when error variances are larger and the group size is small. 主办单位：彩神大发彩票代理统计学院  中国经济统计研究中心 欢迎广大师生踊跃参加！ 【关闭窗口】

 学习贯彻十九届四中全会精神 （2019-11-05）

 关于我校WEBVPN开通测试的公告 2019-11-20
 关于举办“天财•博观大讲堂”讲座的通知 2019-11-21
 “情绪自由——从正视情绪开始”心声不凡第二期活动招募通知 2019-11-20
 关于举办伦敦政治经济学院暑期课程项目介绍讲座的通知 2019-11-19
 关于举办“天财统计大讲堂”讲座的通知 2019-11-12
 关于举办第二届（2019）网络平台治理论坛的通知 2019-11-12