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Lack-of-fit tests for quantile regression models
澳门新葡8455最新网站:2017年05月04日 09:10 点击数:

报告人:冯兴东

报告地点:澳门新葡8455最新网站四楼学术报告厅

报告澳门新葡8455最新网站:2017年05月06日星期六10:10-10:40

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报告摘要:

This paper novelly transforms lack-of-fit tests for parametric quantile regression models into checking the equality of two conditional distributions of covariates. We then can borrow these successful test statistics from the rich literature of two-sample problems, and this gives us much flexibility in constructing a reliable test according our experiences on covariates. As an illustration, three two-sample test statistics are considered, and it will lead to He and Zhu's (2003) test when a Cramer-von Mises test statistic is employed. The second one is a practical two-sample test statistic especially for multivariate distributions, and the resulting test is still applicable in real applications when the number of covariates is moderate or even large. In the last case, we provide a lack-of-fit test based on two-sample tests on moments for the high-dimensional data. Its usefulness is demonstrated by simulation experiments and a real example.

主讲人概况:

冯兴东现任教于上海财经大学,教授。

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