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Nonparametric Tests for Equality of Conditional Distributions

发布日期:2024-10-21点击: 发布人:统计与数学学院

报告题目:Nonparametric Tests for Equality of Conditional Distributions

主讲人:宋晓军副教授(北京大学)

时间:2024年10月21日(周一)10:00 a.m.

地点:北院卓远楼305会议室

主办单位:统计与数学学院

摘要:We propose nonparametric tests for the equality of two conditional distributions. To avoid the estimation of conditional density functions, we transform the null hypothesis into an equivalent characterization that a function involving only unconditional expectations equals zero everywhere. Based on an empirical analog of this function, which is $\sqrt{N}$-consistent and converges weakly to a Gaussian limit, we construct the Kolmogorov-Smirnov (KS) and Cramer-von Mises (CvM) statistics. The critical values are computed by a multiplier bootstrap procedure. The proposed KS and CvM tests are proved to be asymptotically size-controlled and consistent against any fixed alternative, and we also study the local power. Monte Carlo experiments illustrate good performances of these tests in finite samples.

主讲人简介:

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,博士生导师,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。论文发表在Annals of Applied Statistics,Biometrics,Econometric Theory,Journal of Applied Econometrics,Journal of Business & Economic Statistics和Journal of Econometrics等国际期刊。主持和参与自然科学基金面上项目和重点项目等。自2020年1月起担任Economic Modelling副主编。