Hi, I have been using R for close to two years now and have grown quite comfortable with the language. I am presently trying to implement an optimization routine in R (Newton Rhapson). I have some R functions that calculate the gradient and hessian (pre requisite matrices) fairly efficiently. Now, I have to call this function iteratively until some convergance criterion is reached. I think the standard method of doing this in most programming languages is a while loop. However, I know R can get pretty slow when you use loops. In order to make this efficient, I want to transfer this part of my code to a more efficient programming language like c++ or c. However, I have been trying to learn this all day without any luck. I found a package called Rcpp that makes this easier. However, it seems some functional knowledge of writing R packages is a pre requisite. I tried to follow the standard manual for doing this, but could not find a simple example to get me started. I know I am supposed to make a cpp file and put it some where before it can be called from R, but I'm confused as to how this can be done.
My requirement is to start with a parameter vector, update it according to the gradient and hessian, check if the parameter satisfies some convergance criterion and continue doing this until it does. Is there a way to efficiently do this through an R function (replicate?). The problem is that the number of iterations is not fixed. If there is no function in R, is there a way I can quickly use Rcpp or some thing to have this last part of my code in a C or C++ program which repeatedly calls my R functions for updating the parameters? -- Thanks in advance, Rohit Mob: 91 9819926213 [[alternative HTML version deleted]] ______________________________________________ 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.