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Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 1. Theory

Water Resources Research

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https://doi.org/10.1029/WR018i004p00965

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Abstract

Prior information on the parameters of a groundwater flow model can be used to improve parameter estimates obtained from nonlinear regression solution of a modeling problem. Two scales of prior information can be available: (1) prior information having known reliability (that is, bias and random error structure) and (2) prior information consisting of best available estimates of unknown reliability. A regression method that incorporates the second scale of prior information assumes the prior information to be fixed for any particular analysis to produce improved, although biased, parameter estimates. Approximate optimization of two auxiliary parameters of the formulation is used to help minimize the bias, which is almost always much smaller than that resulting from standard ridge regression. It is shown that if both scales of prior information are available, then a combined regression analysis may be made.

Additional publication details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 1. Theory
Series title:
Water Resources Research
DOI:
10.1029/WR018i004p00965
Volume:
18
Issue:
4
Year Published:
1982
Language:
English
Publisher:
American Geophysical Union
Description:
12 p.
First page:
965
Last page:
976