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dc.contributor.authorHu, W.en
dc.contributor.authorXie, J.en
dc.contributor.authorChau, Henryen
dc.contributor.authorSi, B. C.en
dc.identifier.citationHu, W. Xie, J. Chau, H. W. & Si, B. C. (2015). Evaluation of parameter uncertainties in nonlinear regression using Microsoft Excel Spreadsheet. Environmental Systems Research, 4:4. DOI 10.1186/s40068-015-0031-4en
dc.description.abstractBackground Nonlinear relationships are common in the environmental discipline. Spreadsheet packages such as Microsoft Excel come with an add-on for nonlinear regression, but parameter uncertainty estimates are not yet available. The purpose of this paper is to use Monte Carlo and bootstrap methods to estimate nonlinear parameter uncertainties with a Microsoft Excel spreadsheet. As an example, uncertainties of two parameters (α and n) for a soil water retention curve are estimated. Results The fitted parameters generally do not follow a normal distribution. Except for the upper limit of α using the bootstrap method, the lower and upper limits of α and n obtained by these two methods are slightly greater than those obtained using the SigmaPlot software which linearlizes the nonlinear model. Conclusions Since the linearization method is based on the assumption of normal distribution of parameter values, the Monte Carlo and bootstrap methods may be preferred to the linearization method.en
dc.publisherSpringerOpen journalsen
dc.relationThe original publication is available from - SpringerOpen journals - -
dc.rights© 2015 Hu et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.en
dc.subjectMonte Carloen
dc.subjectsoil water retentionen
dc.subjectparameter uncertaintyen
dc.titleEvaluation of parameter uncertainties in nonlinear regression using Microsoft Excel Spreadsheeten
dc.typeJournal Article
lu.contributor.unitLincoln Universityen
lu.contributor.unitFaculty of Agriculture and Life Sciencesen
lu.contributor.unitDepartment of Soil and Physical Sciencesen
lu.contributor.unitResearch Management Officeen
lu.contributor.unit/LU/Research Management Office/2018 PBRF Staff groupen
dc.subject.anzsrc0803 Computer Softwareen
dc.subject.anzsrc0802 Computation Theory and Mathematicsen
dc.relation.isPartOfEnvironmental Systems Researchen
pubs.organisational-group/LU/Agriculture and Life Sciences
pubs.organisational-group/LU/Agriculture and Life Sciences/SOILS
pubs.organisational-group/LU/Research Management Office
pubs.organisational-group/LU/Research Management Office/2018 PBRF Staff group

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