Deepest regression in analytical chemistry

被引：0
|
作者：
Rousseeuw, PJ
Van Aelst, S
Rambali, B
Smeyers-Verbeke, J
机构：
[1] Univ Instelling Antwerp, Dept Math & Comp Sci, B-2610 Antwerp, Belgium
[2] Free Univ Brussels, Inst Pharmaceut, B-1090 Brussels, Belgium
来源：
ANALYTICA CHIMICA ACTA | 2001年 / 446卷 / 1-2期
关键词：
Michaelis-Menten model; regression depth; robustness;
D O I：
暂无
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Recently the concept of regression depth has been introduced [J. Am. Stat. Assoc. 94 (1999) 388]. The deepest regression (DR) is a method for linear regression which is defined as the fit with the best depth relative to the data. In this paper we explain the properties of the DR and give some applications of DR in analytical chemistry which involve regression through the origin, polynomial regression, the Michaelis-Menten model, and censored responses. (C) 2001 Elsevier Science B.V. All rights reserved.
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页码：245 / 256
页数：12
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