MODERN NONLINEAR-REGRESSION METHODS

被引:55
|
作者
FRANK, IE
机构
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.
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页码:1 / 19
页数:19
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