Why fails nls with "singular gradient" here? I post a minimal example on the bottom and would be very happy if someone could help me. Kind regards,
########### # define some constants smallc <- 0.0001 t <- seq(0,1,0.001) t0 <- 0.5 tau1 <- 0.02 # generate yy(t) yy <- 1/2 * ( 1- tanh((t - t0)/smallc) * exp(-t / tau1) ) + rnorm(length(t))*0.01 # show the curve plot(x=t, y=yy, pch=18) # prepare data dd <- data.frame(y=yy, x=t) nlsfit <- nls(data=dd, y ~ 1/2 * ( 1- tanh((x - ttt)/smallc) * exp(-x / tau2) ), start=list(ttt=0.4, tau2=0.1) , trace=TRUE) # get error: # Error in nls(data = dd, y ~ 1/2 * (1 - tanh((x - ttt)/smallc) * exp(-x/tau2)), : # singular gradient -- Jonas Stein <n...@jonasstein.de> ______________________________________________ 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.
