Please use this identifier to cite or link to this item:
Title: The Adaptation of Curvature Measures to Assess Nonlinearity in 'Functionless' Models
Contributor(s): Thomas, K (author); Ellem, Bernard (author)
Corporate Author: School of Mathematics, Statistics and Computer Science
Publication Date: 2006
Handle Link:
Abstract: Bates and Watts (1980) presented curvature measures for assessing the effects of nonlinearity in regression models. The practical and routine methods for assessing this nonlinearity during data analysis employ the methodology of profile plots and traces. (Bates and Watts, 1988). In their book on Nonlinear Regression these profiling methods were clearly demonstrated with the fitting of nonlinear regression models, compartmental models and multiresponse models to data. This paper demonstrates that these profile methods can be extended to models similar to the above. This new class of models does not require that an analytical function or mathematical form of solution be specified. Such 'functionless' models generally require numerical schemes for their solution.
Publication Type: Report
Publisher: School of Mathematics, Statistics and Computer Science: The University of New England
Place of Publication: Armidale, Australia
Field of Research (FOR): 010499 Statistics not elsewhere classified
Socio-Economic Outcome Codes: 970101 Expanding Knowledge in the Mathematical Sciences
HERDC Category Description: R1 Contract Report
Series Name: Research and Technical Reports
Statistics to Oct 2018: Visitors: 163
Views: 168
Downloads: 0
Appears in Collections:Report

Files in This Item:
2 files
File Description SizeFormat 
Show full item record

Page view(s)

checked on May 2, 2019
Google Media

Google ScholarTM


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.