I hardly see how your reply addressed my question or any part of it. It looks to me that it was simply assumed that I did not perform any search before posting.
________________________________ From: Bert Gunter <bgunter.4...@gmail.com> Sent: Tuesday, July 28, 2020 11:30 To: Sebastien Bihorel <sebastien.biho...@cognigencorp.com> Cc: r-help@r-project.org <r-help@r-project.org> Subject: Re: [R] Nonlinear logistic regression fitting You said: "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." My reply responded to that. AFAIK, opinions on packages are off topic here. Try stats.stackexchange.com<http://stats.stackexchange.com> for that. 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 8:19 AM Sebastien Bihorel <sebastien.biho...@cognigencorp.com<mailto:sebastien.biho...@cognigencorp.com>> wrote: Thank you for your subtle input, Bert... as usual! This is literally the search I conducted and spent 2 hours on before posting to R-help. I was asking for expert opinions, not for search engine FAQ! Thank anyways ________________________________ From: Bert Gunter <bgunter.4...@gmail.com<mailto:bgunter.4...@gmail.com>> Sent: Tuesday, July 28, 2020 11:12 To: Sebastien Bihorel <sebastien.biho...@cognigencorp.com<mailto:sebastien.biho...@cognigencorp.com>> Cc: r-help@r-project.org<mailto:r-help@r-project.org> <r-help@r-project.org<mailto:r-help@r-project.org>> Subject: Re: [R] Nonlinear logistic regression fitting Search! ... for "nonlinear logistic regression" at rseek.org<http://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<mailto: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<mailto: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.
