報告題目：Neyman's Smooth Tests for Nonparametric Models（非參數(shù)模型的Neyman光滑檢驗）
主講人：宋曉軍副教授（北京大學）
時間：2023年4月21日（周五）10:00 a.m.
地點：北院卓遠樓305會議室
主辦單位：統(tǒng)計與數(shù)學學院
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.
主講人簡介：
宋曉軍，男，北京大學光華管理學院商務統(tǒng)計與經濟計量系副教授，博士生導師，西班牙馬德里卡洛斯三世大學經濟學博士。主要研究興趣是理論計量經濟學，包括非參數(shù)/半參數(shù)方法，假設檢驗和自助法，以及計量經濟學的應用等。論文發(fā)表在Econometric Theory，Journal of Applied Econometrics，Journal of Business & Economic Statistics和Journal of Econometrics等國際期刊。主持和參加自然科學基金面上項目和國家重點專項等。目前擔任Economic Modelling副主編。
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