Title of article
Modern nonlinear regression methods
Author/Authors
Frank ، نويسنده , , Ildiko E.، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 1995
Pages
19
From page
1
To page
19
Abstract
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.
Journal title
Chemometrics and Intelligent Laboratory Systems
Serial Year
1995
Journal title
Chemometrics and Intelligent Laboratory Systems
Record number
1459271
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