A comparison of methods of fitting several models to nutritional response data

dc.contributor.author	Vedenov, D	en
dc.contributor.author	Pestit, GM	en
dc.date.accessioned	2014-06-06T06:48:03Z
dc.date.available	2014-06-06T06:48:03Z
dc.date.issued	2008	en
dc.identifier.issn	00218812	en
dc.identifier.uri	http://dx.doi.org/10.2527/jas.2007-0536	en
dc.identifier.uri	http://62.217.125.90/xmlui/handle/123456789/3934
dc.subject	Mathematical modeling	en
dc.subject	Nutritional requirement	en
dc.subject.other	algorithm	en
dc.subject.other	animal	en
dc.subject.other	animal food	en
dc.subject.other	article	en
dc.subject.other	biological model	en
dc.subject.other	comparative study	en
dc.subject.other	computer	en
dc.subject.other	computer program	en
dc.subject.other	mathematics	en
dc.subject.other	nutritional requirement	en
dc.subject.other	physiology	en
dc.subject.other	statistical model	en
dc.subject.other	Algorithms	en
dc.subject.other	Animal Feed	en
dc.subject.other	Animal Nutrition Physiology	en
dc.subject.other	Animals	en
dc.subject.other	Computers	en
dc.subject.other	Mathematics	en
dc.subject.other	Models, Biological	en
dc.subject.other	Models, Statistical	en
dc.subject.other	Nutritional Requirements	en
dc.subject.other	Software	en
dc.title	A comparison of methods of fitting several models to nutritional response data	en
heal.type	journalArticle	en
heal.identifier.primary	10.2527/jas.2007-0536	en
heal.publicationDate	2008	en
heal.abstract	A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data. ©2008 American Society of Animal Science. All rights reserved.	en
heal.journalName	Journal of Animal Science	en
dc.identifier.issue	2	en
dc.identifier.volume	86	en
dc.identifier.doi	10.2527/jas.2007-0536	en
dc.identifier.spage	500	en
dc.identifier.epage	507	en