[R] Nonlinear logistic regression fitting

[Rasmus Liland]

Dear Sebastien,

On 2020-07-28 14:13 +0000, Sebastien Bihorel 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.

I found base stats has the function 
stats::SSmicmen, also this page[1] 
mentions stats::nls ... 

I found cardioModel::cardioModel ...  
You need Google V8[3] which takes 
forever to build.

Also the emaxmodel vignette[4] might be 
useful, as it mentions both EC50 and 
Emax.

Best,
Rasmus

[1] https://dataconomy.com/2017/08/nonlinear-least-square-nonlinear-regression-r/
[2] https://www.rdocumentation.org/packages/cardioModel/versions/1.4/topics/cardioModel
[3] https://v8.dev/
[4] https://cran.r-project.org/web/packages/rstanemax/vignettes/emaxmodel.html