主 講 人：Wolfgang Hardle 教授  (Institute for Statistics and Econometrics Humboldt-University, Germany) 
講    題：Local Quantile Regression
日    期：99年11月30日（星期二）下午4:00 – 4:50
地    點：數學系(科學館S433室)
摘    要：
Conditional quantile curves provide a comprehensive picture of a response 
contingent on explanatory variables. Quantile regression is a technique to 
estimate such curves. In a flexible modeling framework, a specific form of the 
quantile is not a priori fixed. Indeed, the majority of application do not per se 
require specific functional forms. This motivates a local parametric rather than a 
global fixed model fitting approach. A nonparametric smoothing estimate of the 
conditional quantile curve requires to consider a balance between local 
curvature and variance. In this paper, we analyze a method based on a local 
model selection that provides an adaptive estimates. Theoretical properties on 
mimicking the oracle choice are offered and applications to VaR are presented.
 
Keywords: Conditional quantiles; Asymmetric Laplace distribution; Exponential Risk Bounds; Adaptive Bandwidth Selection.