Abstract
The explicit form of a non-linear model may not be known. However, in some cases, it is known that there is an underlying non-linear relationship, which varies from individual to individual by means of differing scale parameters; when the form of the underlying relationship is known, this is known as a parallel curve analysis. This analysis can be extended to fit general functions (general parallel curves) that are only specified at a set of x-values. Such models can be fitted using Singular Value Decomposition. Two examples of the use of general parallel curves are presented. The first involves a study of wheat growth, the second, the detection of pesticide interactions.
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© 1998 Springer-Verlag Berlin Heidelberg
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Brain, P. (1998). Using Singular Value Decomposition in Non-Linear Regression. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_21
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DOI: https://doi.org/10.1007/978-3-662-01131-7_21
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
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