MODERN NONLINEAR-REGRESSION METHODS

被引：58

作者：

FRANK, IE

机构：

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1995年 / 27卷 / 01期

关键词：

D O I：

10.1016/0169-7439(94)00005-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Several nonparametric nonlinear regression models are discussed and compared. Instead of forcing a predefined analytical form on the data, these methods approximate the underlying nonlinear function using smoothers or splines on the training data set. The performances of these methods are compared in a Monte Carlo simulation study and illustrated on a data set from food chemistry.

引用

页码：1 / 19

页数：19

共 12 条

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[2]

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