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.4567 at gmail.com> Sent: Tuesday, July 28, 2020 11:12 To: Sebastien Bihorel <Sebastien.Bihorel at cognigencorp.com> Cc: r-help at r-project.org <r-help at 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 at r-project.org<mailto:r-help at 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 at r-project.org<mailto:R-help at 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]]
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 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.Bihorel at 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.4567 at gmail.com> > *Sent:* Tuesday, July 28, 2020 11:12 > *To:* Sebastien Bihorel <Sebastien.Bihorel at cognigencorp.com> > *Cc:* r-help at r-project.org <r-help at r-project.org> > *Subject:* Re: [R] Nonlinear logistic regression fitting > > 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 at 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 at 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]]
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.4567 at gmail.com> Sent: Tuesday, July 28, 2020 11:30 To: Sebastien Bihorel <Sebastien.Bihorel at cognigencorp.com> Cc: r-help at r-project.org <r-help at 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.Bihorel at cognigencorp.com<mailto:Sebastien.Bihorel at 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.4567 at gmail.com<mailto:bgunter.4567 at gmail.com>> Sent: Tuesday, July 28, 2020 11:12 To: Sebastien Bihorel <Sebastien.Bihorel at cognigencorp.com<mailto:Sebastien.Bihorel at cognigencorp.com>> Cc: r-help at r-project.org<mailto:r-help at r-project.org> <r-help at r-project.org<mailto:r-help at 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 at r-project.org<mailto:r-help at 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 at r-project.org<mailto:R-help at 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]]
Did you try searching for "Michaelis" on rseek.org? It seems like there are many hits that might be pertinent to your query. If none is pertinent, maybe saying why they are not sufficient will help others see how their "expert opinions" can help you. HTH, Chuck> On Jul 28, 2020, at 8:19 AM, Sebastien Bihorel via R-help <r-help at r-project.org> 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.4567 at gmail.com> > Sent: Tuesday, July 28, 2020 11:12 > To: Sebastien Bihorel <Sebastien.Bihorel at cognigencorp.com> > Cc: r-help at r-project.org <r-help at 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 at r-project.org<mailto:r-help at 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 at r-project.org<mailto:R-help at 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]] >