An interior point algorithm for nonlinear quantile regression

被引：203
|
作者：
Koenker, R
Park, BJ
机构：
[1] Department of Economics, University of Illinois, Champaign
来源：
JOURNAL OF ECONOMETRICS | 1996年 / 71卷 / 1-2期
基金：
美国国家科学基金会;
关键词：
quantile regression; nonlinear regression; linear programming; interior point algorithms; nonlinear programming;
D O I：
10.1016/0304-4076(96)84507-6
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
A new algorithm for computing quantile regression estimates for problems in which the response function is nonlinear in parameters is described. The nonlinear I, estimation problem is a special (median) case. The algorithm is closely related to recent developments on interior point methods for solving linear programs. Performance of the algorithm on a variety of test problems including the censored linear quantile regression problem of Powell (1986) is reported.
引用
收藏
页码：265 / 283
页数：19
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