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Information criteria for latent factor models: a study with general factor pervasiveness and adaptivity
澳门新葡8455最新网站:2019年10月30日 16:28 点击数:

报告人:郭潇

报告地点:澳门新葡8455最新网站415会议室

报告澳门新葡8455最新网站:2019年11月01日星期五10:00-11:00

邀请人:郑术蓉

报告摘要:

We study the information criteria for latent factor models, allowing large number of variables diverging with the sample size. Without requiring the factor pervasiveness condition as in existing studies, our investigation accommodates generic schemes that broadly and flexibly characterize the contributions from the latent common factors. We dedicatedly analyze the properties of the information criteria, and provide new insights on the fundamental importance from adequately incorporating the impact due to different strength of the factor pervasiveness. Based on the analysis, we then propose a class of new information criteria, adaptive to the strength of the factor pervasiveness, for identifying the number of the latent common factors. Our theory establishes the consistency of the proposed adaptive information criteria in correctly determining the number of the latent factors. Our analysis reveals that the adaptivity to the factor pervasiveness is indeed a key for the information criteria to be consistent in broad settings. As another new discovery, we show that when the strength of the factor pervasiveness is weak below certain level, then correctly determining the number of the latent factors is not feasible with information criteria. We demonstrate the performance of our new adaptive information criteria with extensive numerical examples including simulations and real data analysis.

主讲人概况:

郭潇,中国科学技术大学,统计与金融系,特任副研究员。毕业于威斯康星大学麦迪逊分校统计系。主要研究方向为高维协方差矩阵估计与推断、稳健估计与推断、高维因子模型、变量选择等。学术论文发表在Statistica Sinica,Technometrics等期刊。

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