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報(bào)告題目：Neyman's Smooth Tests for Nonparametric Models（非參數(shù)模型的Neyman光滑檢驗(yàn)）

主講人：宋曉軍副教授（北京大學(xué)）

時(shí)間：2023年4月21日（周五）10:00 a.m.

地點(diǎn)：北院卓遠(yuǎn)樓305會(huì)議室

主辦單位：統(tǒng)計(jì)與數(shù)學(xué)學(xué)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(jiǎn)介：

宋曉軍,，男，北京大學(xué)光華管理學(xué)院商務(wù)統(tǒng)計(jì)與經(jīng)濟(jì)計(jì)量系副教授,，博士生導(dǎo)師，西班牙馬德里卡洛斯三世大學(xué)經(jīng)濟(jì)學(xué)博士。主要研究興趣是理論計(jì)量經(jīng)濟(jì)學(xué),，包括非參數(shù)/半?yún)?shù)方法，假設(shè)檢驗(yàn)和自助法,，以及計(jì)量經(jīng)濟(jì)學(xué)的應(yīng)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(guó)際期刊,。主持和參加自然科學(xué)基金面上項(xiàng)目和國(guó)家重點(diǎn)專(zhuān)項(xiàng)等,。目前擔(dān)任Economic Modelling副主編。