The application modules OPTMUM and MAXLIK seem to share a lot of features. Can someone explain the differences in functionality between the two modules?
A. OPTMUM minimizes a general, user-provided function, whereas MAXLIK specializes that function to the log-likelihood function. The important difference is that MAXLIK is designed to handle a data set. Among GAUSS users the most common type of optimization is maximum likelihood estimation, and MAXLIK significantly reduces the amount of programming in this case. In addition, MAXLIK adds the BHHH descent method which only makes sense when there is a data set. I would like to add, though, that the BHHH descent method is inferior to BFGS and DFP, and is included only because it appears to be quite popular among econometricians. The BHHH method, a type of “scoring” method, relies on the equivalence of the cross-product of the first derivatives with the Hessian; i.e., the second derivatives. As H. White has shown, this equivalence breaks down under misspecification. All researchers know that many more misspecified models are estimated than correctly specified ones, and thus one should expect
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