An interior point algorithm for nonlinear quantile regression

被引：209

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

页码：265 / 283

页数：19

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