Hello, I'm trying to fit experimental data with a model and nls. For some experiments, I have data with x from 0 to 1.2 and the fit is quite good. But it can happen that I have data only the [0,0.8] range (see the example below) and, then, the fit is not correct.
I would like to add a constraint, for example : the second derivative must be positive. But I don't know how to add this to nls and, in fact, I'm not sure that it is possible. If not, could you give me a package and/or a function (and/or a complete solution, which will be great ...) ? Thanks in advance for your help, Have a good day, Ptit Bleu. ------------------------------------------------------------------------------------------------------------- #The experimental data : http://r.789695.n4.nabble.com/file/n4634705/nlstest_data.txt nlstest_data.txt #The script library(lattice) dftest<-read.table("nlstest_data.txt", sep=";", dec=".", as.is=T, header=T) nlsfit<-coefficients(nls(y ~ F+A*(x-1)+B*log(x)+C*(x-1)*(x-1)+D*log(x)*log(x), data=dftest, start = list(A=-0.06,B=0.48,C=0.89,D=0.03,F=1), control=list(maxiter=200, tol=0.01))) # Coefficients : # A B C D F # -0.06098888 0.48632458 0.89397997 0.02978641 5.00743745 plot(dftest$x,dftest$y,pch=20, col="red", xlim=c(0,1.2)) seqx<-seq(0,1.2,by=0.0125) # There must me a way with predict, but I didn't manage to use it points(seqx,nlsfit[5]+nlsfit[1]*(seqx-1)+nlsfit[2]*log(seqx)+nlsfit[3]*(seqx-1)*(seqx-1)+nlsfit[4]*log(seqx)*log(seqx),pch=20,col="black",type="l",lwd=2) #The result of the fit : http://r.789695.n4.nabble.com/file/n4634705/nlstest_graph.png -- View this message in context: http://r.789695.n4.nabble.com/add-constraints-to-nls-or-use-another-function-tp4634705.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.
