Update: The original question is: Is there an R function using the same algorithm implemented in the "lsqnonlin" function in matlab? However, the answer is more related to searching a function in R. I think the answer is in general very helpful for R users. So I edited the title but asked the original question again here: In R, how to do nonlinear least square optimization which involves solving differential equations?
I am doing nonlinear least-square optimizations and found that the matlab function lsqnonlin
performs better than all the optimization algorithms I tried in R (including the algorithms in function optimx
, nlm
, nlminb
, solnp
, etc.) in the sense that it is faster and found the "more correct" solution.
However, I did not find an implementation of the 'trust-region-reflective' algorithm in R that is used in Matlab. Does someone know if there is already an implementation? Also, is it always true that the 'trust-region-reflective' algorithm is a better algorithm for this kind of optimization?
It sounds like
lsqnonlin
in thepracma
package is what you're looking for.I recommend installing the
sos
package for R. Its purpose is to help you answer questions like 'Is there a function out there that does this?'.findFn
in this package will search what's on CRAN for the term you supply.