On Apr 17, 2012, at 06:23 , Francisco Mora Ardila wrote: > Hi > > I´m trying to fit a nonlinear model to a derivative of the logistic function > > y = a/(1+exp((b-x)/c)) (this is the parametrization for the SSlogis function > with nls) > > The derivative calculated with D function is: > >> logis<- expression(a/(1+exp((b-x)/c))) >> D(logis, "x") > a * (exp((b - x)/c) * (1/c))/(1 + exp((b - x)/c))^2 > > So I enter this expression in the nls function: > > ratelogis <- nls(Y ~ a*(exp((b-X)/c)*(1/c))/(1 + exp((b-X)/c))^2, > start=list(a = 21.16322, b = 8.83669, c = 2.957765), > ) > > The data is: > >> Y > [1] 5.5199668 1.5234525 3.3557000 6.7211704 7.4237955 1.9703127 > [7] 4.3939336 -1.4380091 3.2650180 3.5760906 0.2947972 1.0569417 >> X > [1] 1 0 0 4 3 5 12 10 12 100 100 100 > > The problem is that I got the next error: > > Error en nls(Y ~ a * (exp((b - X)/c) * (1/c))/(1 + exp((b - X)/c))^2, : > step factor 0.000488281 reduced below 'minFactor' of 0.000976563 > > I trien to change the minFactor using the control argument inside nls > > control=nls.control(maxiter=50, tol=1e-5, minFactor = 1/2048 > > but got a new error message: > > > Error en nls(Y ~ a * (exp((b - X)/c) * (1/c))/(1 + exp((b - X)/c))^2, : > step factor 0.000244141 reduced below 'minFactor' of 0.000488281 > > So it seems that as I modify minFactor, the step factor reduces also and I > can never > reach a solution. > > Does anybody Know what am I doing wrong? Is there a problem with the formula? > How can I > solve it? I tried some suggestions on R-help related topics but did not work.
(Please don't send private messages. I don't do free consulting outside of the mailing lists.) With nls(), there's really no substitute for good data and good starting values. Did you actually try plotting those data? At best, they are extremely noisy. How did you obtain the starting values? They seem remarkably accurate for something that fits data so poorly. What is happening is that the algorithm shoots off into a region of the parameter space where it can't make any progress: > ratelogis <- nls(Y ~ a*(exp((b-X)/c)*(1/c))/(1 + exp((b-X)/c))^2,+ > start=list(a = 21.16322, b = 8.83669, c = 2.957765),+ trace=TRUE) 151.098 : 21.163220 8.836690 2.957765 127.1149 : 103.49326 11.43274 20.29663 111.344 : 833.02386 -45.86244 140.32985 111.3375 : 978.97214 -76.20571 159.90833 111.3374 : 1097.1376 -101.6771 174.2037 111.3228 : 1179.8451 -119.7416 183.3794 Notice that the "b" parameter which is supposed to be the maximum point starts off well to the right of the position of the largest Y values, then shoots into large negative values. With a little eyeballing, I can do better: > ratelogis <- nls(Y ~ a*(exp((b-X)/c)*(1/c))/(1 + exp((b-X)/c))^2, + start=list(a = 40, b = 3.5, c = 10),trace=T) 139.5173 : 40.0 3.5 10.0 97.28614 : 26.513424 4.052639 2.267709 81.53127 : 32.384910 3.473411 2.307504 65.11387 : 39.53542 3.01097 2.07678 50.66328 : 36.223529 2.590102 1.133965 50.50921 : 35.984466 2.565698 1.067731 50.50162 : 36.149993 2.573420 1.081673 50.50145 : 36.129962 2.572195 1.079504 50.50144 : 36.133656 2.572402 1.079862 50.50144 : 36.133061 2.572368 1.079803 However, the fit isn't exactly stellar. Try this: X <- c(1, 0, 0, 4, 3, 5, 12, 10, 12, 100, 100, 100) Y <- c(5.5199668, 1.5234525, 3.3557, 6.7211704, 7.4237955, 1.9703127, 4.3939336, -1.4380091, 3.265018, 3.5760906, 0.2947972, 1.0569417) plot(X,Y) ratelogis <- nls(Y ~ a*(exp((b-X)/c)*(1/c))/(1 + exp((b-X)/c))^2, start=list(a = 40, b = 3.5, c = 10),trace=T) x0 <- seq(0,100,,1000) lines(x0,predict(ratelogis,newdata=data.frame(X=x0))) lines(x0,evalq(a*(exp((b-X)/c)*(1/c))/(1 + exp((b-X)/c))^2,envir=list(a = 21.16322, b = 8.83669, c = 2.957765, X=x0)), lty="dashed") -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.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.
