报告人：Prof. Dr. Wolfgang K. Haerdle德国柏林洪堡大学 Ladislaus von Bortkiewicz 统计学讲席教授, 统计系主任

报告时间：2013年5月23日上午10点

报告地点：数学楼二楼学术报告厅

摘 要: Quantile regression is in the focus of many estimation techniques and is an important tool in data analysis. When it comes to nonparametric specifications of the conditional quantile (or more generally tail) curve one faces, as in mean regression, a dimensionality problem. We propose a projection based single index model specification. For very high dimensional regressors X one faces yet another dimensionality problem and needs to balance precision vs. dimension. Such a balance may be achieved by combining semiparametric ideas with variable selection techniques.