时间：2021年11月11日（周四）下午1:30-3:00

地点：博学楼1007

主持人：林蔚（国际经济贸易学院数量经济学系）

讲座题目：Neyman's Smooth Tests for Nonparametric Models

讲座摘要：Neyman （1937）'s smooth test has proven to be an extremely valuable tool in the long history of statistical hypothesis testing. Smooth tests are inspired from the probability integral transform （PIT）; for example, smooth tests have been proposed to assess the goodness-of-fit of various popular parametric distributions. Nevertheless, the majority of the exisiting literature focuses on PIT in parametric models, even though Neyman （1937）'s idea is general and easily applicable to PIT constructed from nonparametric models. In this talk I mainly discuss the promising aspects of the smooth tests for nonparametric models. In particular, I focus on smooth tests for （i） conditional independence, （ii） copula independence, and （iii） the equality of （conditional） distributions as well as the equality of copulas in the two-sample settings.

讲座人简介：宋晓军，北京大学光华管理学院商务统计与经济计量系副教授，西班牙马德里卡洛斯三世大学经济学博士。主要研究兴趣是理论计量经济学，包括非参数，半参数方法，假设检验和自助法，以及计量经济学的应用等。主要研究成果发表在Journal of Econometrics，Journal of Business and Economic Statistics，Econometric Theory等国际学术期刊上。

讲座人主页：https://www.gsm.pku.edu.cn/faculty/sxj/