Dear list-members, I have done optimization of 3 parameters by maximum likelihood method using conjugate gradient as optimizer. Since I have the reported value of the parameters from an article, I can validate the result of the optimized parameters. The problem is that optimizer converges to the desirable value. (as reported in the article) only for a certain starting value.
If the staring value of the parameters are like (2,1,1) then the value of parameters the function converges is $par [1] -0.4169408 -0.2800828 2.9614670 And the value is close to the value of article reported in the article Vs = 0.4861 ; Vn = 0.1478 and m is some positive value (no value mentioned in the article) And If I fine tune the starting value from (2,1,1) to (1.949,1.13,1) then I get the value of the parameters very close to the one reported. $par [1] -0.4700892 -0.1428245 2.9614670 Now the question is how I can find the starting values for the test experiment for which I am going to implement this optimization procedure. Is there any function to be wrapped with optim() to find the right starting value. Regards, B.Nataraj ______________________________________________ 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.
