[R] Nonlinear logistic regression fitting
bgunter@4567 @end|ng |rom gm@||@com
Tue Jul 28 17:12:29 CEST 2020
... for "nonlinear logistic regression" at rseek.org.
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On Tue, Jul 28, 2020 at 7:25 AM Sebastien Bihorel via R-help <
r-help using r-project.org> wrote:
> I need to fit a logistic regression model using a saturable
> Michaelis-Menten function of my predictor x. The likelihood could be
> expressed as:
> L = intercept + emax * x / (EC50+x)
> Which I guess could be expressed as the following R model
> ~ emax*x/(ec50+x)
> As far as I know (please, correct me if I am wrong), fitting such a model
> is to not doable with glm, since the function is not linear.
> A Stackoverflow post recommends the bnlr function from the gnlm (
> I would be grateful for any opinion on this package or for any alternative
> recommendation of package/function.
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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