Heteroscedastic nonlinear regression models with random effects

dc.contributor.author	Gilberg, Frank	de
dc.contributor.author	Urfer, Wolfgang	de
dc.date.accessioned	2004-12-06T18:38:57Z
dc.date.available	2004-12-06T18:38:57Z
dc.date.issued	1998	de
dc.description.abstract	We discuss an extansion of the nonlinear random effects model from Lindstrom and Bates (1990) by adding a flexible transformation to both sides of the model (see Carroll and Ruppert (1988)) and describe a procedure for parameter estimation. This method combines pseudo maximum likelihood estimators for the transform-both-sides and weighting model and maximum likelihood (or restricted maximum likelihood) estimatiors for the linear mixed effects models. A validation of this new method is performed by analyzing a simulated set of enzyme kinetic data published by Jones (1993).	en
dc.format.extent	1456179 bytes
dc.format.extent	1784706 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/4880
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5320
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	enzyme kinetics	en
dc.subject	nonlinear regression	en
dc.subject	Pseudo likelihood estimation	en
dc.subject	random effects	en
dc.subject	repeated measures data	en
dc.subject	transformation and weighting	en
dc.subject.ddc	310	de
dc.title	Heteroscedastic nonlinear regression models with random effects	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access
eldorado.dnb.deposit	true

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