Search! ... for "nonlinear logistic regression" at rseek.org. Bert Gunter
"The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Jul 28, 2020 at 7:25 AM Sebastien Bihorel via R-help < r-help@r-project.org> wrote: > Hi > > 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 ( > https://stackoverflow.com/questions/45362548/nonlinear-logistic-regression-package-in-r)... > I would be grateful for any opinion on this package or for any alternative > recommendation of package/function. > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
