Hi there, I hope someone can help me before I tear all my hair out. I have a set transition intensities and when plotted the curve looks like a gamma density. I want to fit a gamma density curve to these intensities. It is just a curve fitting problem but whats causing the trouble is that I need to use least squares minimization to calculate the parameters for the gamma curve. How do I do this???
The curve will be a truncated gamma function so it will have 3 paramaters a, b, c. I tried to do the following nls(lograte ~ log(c) + a*log(b) + (a-1)*log(age)+b*(age)-lgamma(a), start=list(a=1,b=1,c=1)), where lograte, and age are my data. a,b the gamma parameters and c the parameter we need because we are fitting a truncated distribution. I also tried defining fn = function(p) sum((log(y)-log(dgamma(x,p[1],p[2])*p[3]))^2) a residual sum of squares and using nlm to minimise this and find paramaters but this doesnt work either. Can anyone help me ?? Please :) -- View this message in context: http://www.nabble.com/Fitting-a-Gamma-Curve-tf4068543.html#a11561404 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ [email protected] 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.
