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Quantile Regression for Large-scale Applications
Quantile Regression Large-scale Applications
2013/6/14
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the relationship between the ...
Asymptotics for penalized spline estimators in quantile regression
Asymptotic normality, B-spline,Penalized spline,Quantile regression
2012/11/22
Quantile regression predicts the $\tau$-quantile of the conditional distribution of a response variable given the explanatory variable for $\tau\in(0,1)$. The aim of this paper is to establish the asy...
Local Quantile Regression
local MLE excess bound propagation condition adaptive bandwidth selection.
2012/9/18
Quantile regression is a technique to estimate conditional quantile curves. It pro-vides a comprehensive picture of a response contingent on explanatory variables. In a exible modeling framework, a sp...
Censored quantile regression processes under dependence and penalization
quantile regression Bahadur representation variable selection weak convergence censored data dependent data
2012/9/18
We consider quantile regression processes from censored data under dependent data structures and derive a uniform Bahadur representation for those processes. We also consider cases where the dimension...
Quantile regression when the covariates are functions
Functional data analysis conditional quantiles B-spline functions roughness penalty
2010/4/27
This paper deals with a linear model of regression on quantiles
when the explanatory variable takes values in some functional space and the
response is scalar. We propose a spline estimator of the f...