时间：2019年7月12日(周五)上午09:00-10:00
地点：中山北路校区理科大楼A1514会议室
题目：A projection-based consistent test incorporating dimension-reduction in partial linear models
报告人：Prof. Hua Liang （Department of Statistics，George Washington University）
摘要：We propose a projection-based test to check partially linear models. The proposed test gains dimension reduction and makes the proposed method act as if only one covariate exists in the presence of multiple dimensional regressors. The test is shown to be consistent and can detect the Pitman local alternative hypothetical models. We further derive asymptotic distributions of the proposed test under the null hypothesis, and local and global alternatives. Most importantly, its numerical performance is consistently and remarkably superior to its competitors. Real examples are presented for an illustration.
报告人介绍：
Prof. Hua Liang，乔治•华盛顿大学统计系教授, 曾任美国罗切斯特大学医学院教授。出版英文学术著作2部，发表学术论文 170 多篇。他主持(了)8项美国国家科学基金会(NSF)以及美国国立卫生研究院(NIH)的研究项目。 他是美国统计学会（ASA）会士(fellow)、国际数理统计学会（IMS）会士、英国皇家统计学会（RSS）会士，国际统计学会（ISI）推举委员，也是JASA 等刊物的编委或副主编。