I have questions regarding test=data.frame(cbind(conc=c(25000, 12500, 6250, 3125, 1513, 781, 391, 195, 97.7, 48.4, 24, 12, 6, 3, 1.5, 0.001), il10=c(330269, 216875, 104613, 51372, 26842, 13256, 7255, 3049, 1849, 743, 480, 255, 241, 128, 103, 50)))
nls(log(il10)~A+(B-A)/(1+(conc/xmid )^scal),data=test, + start = list(A=3.5, B=15, + xmid=600,scal=1/2.5)) Nonlinear regression model model: log(il10) ~ A + (B - A)/(1 + (conc/xmid)^scal) data: test A B xmid scal 14.7051665 3.7964534 607.9822962 0.3987786 residual sum-of-squares: 0.1667462 I did not understand how these values A=3.5, B=15,xmid=600,scal=1/2.5 were obtained by Jim in the posting here http://www.mail-archive.com/r-help@stat.math.ethz.ch/msg25500.html. I would appreciate a little help here to understand the 4-parameter logisitic regression for processing of standard curve for ELISA/MUltiplex Immunoassays. Thanks and happy holidays sharad -- View this message in context: http://r.789695.n4.nabble.com/understanding-the-4-parameter-logisitc-regression-tp3091588p3091588.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list 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.