Problems with Optimization
Dear R-helpers, I am having following problem: Let P be an observed quantity, F(...) a function describing P, and e = P - F(...) the error. F(...) is essentially a truncated mean whose value is obtained via integrating from some value X to inf over a probability density with six parameters. That's what usually causes the problem: for certain parameter values, the integral goes very quickly to infinity which the optimization algorithm can't handle. At least nlm() and some of the optim() algorithms cant. The default optim() algorithm appears to be able to handle it (takes very long to converge though) and so is nlminb(). My question is thus not really about which algorithm to use but rather whether there is a 'on error ... do...' catcher in R? I have had a look at try() but I am not quite sure if that is what I am looking for. I essentially look for a command that, in plain English, allows me to specify that if the integral goes to infinity, skip these parameters, and simply continue optimizing into another direction. Is this possible? How do you guys handle situtations like this? Regards Tobias
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