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光滑化分位数过程的估计

  • 演讲者:练恒副教授 香港城市大学数学系

  • 时间:2017-05-25 15:00-16:00

  • 地点:科研教学服务中心703

嘉宾简介:

练恒教授毕业于布朗大学,2007年获应用数学博士学位。他在新加坡南洋理工大学工作了几年,随后迁往悉尼的新南威尔士大学,现在香港城市大学担任副教授。 他的研究兴趣在于半参数估计,高维数据分析和函数型数据分析。

Abstract:

We consider smooth estimation of the conditional quantile process in linear models using penalized splines. For linear quantile regression problems, usually separate models are fitted at a finite number of quantile levels and then information from different quantiles is combined in interpreting the results. We propose a smoothing method based on penalized splines that computes the conditional quantiles all at the same time. We consider both fixed-knots and increasing-knots asymptotics of the estimator and show that it converges to a multivariate Gaussian process. Simulations show that smoothing can result in more accurate estimation of the conditional quantiles. The method is further illustrated on a real data set. Empirically (although not theoretically) we observe that the crossing quantile curves problem can often disappear using the smoothed estimator.