The Least Absolute Deviation Estimation Method of Parameter in Nonlinear Regression Model and Its Feasible Direction Algorithm

被引：0
作者：
Wan Yucheng [1 ]
机构：
[1] Xuzhou AF Coll, Dept Air Mat Management, Xuzhou 221002, Peoples R China
来源：
RECENT ADVANCE IN STATISTICS APPLICATION AND RELATED AREAS, PTS 1 AND 2 | 2011年
关键词：
Nonlinear regression; Parameter estimation; Least absolute deviation estimation; Feasible direction algorithm;
D O I：
暂无
中图分类号：
O1 [数学]; C [社会科学总论];
学科分类号：
03 ; 0303 ; 0701 ; 070101 ;
摘要：
For parameter estimation methods in regression models, the least absolute deviation estimation is more robust than the least square sum estimation in many cases. However, the computation of the least absolute deviation estimation is difficult. In this paper, we reduce the nonlinear least absolute deviation estimation problem to nonlinear programming problem and design a feasible direction algorithm to solve the nonlinear least absolute deviation estimation problem. Numerical example demonstrating the efficiency of this algorithm is given.
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收藏
页码：1338 / 1343
页数：6
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