Maximum Likelihood MT
MaxlikMT contains a set of procedures for the solution of the maximum likelihood problem with bounds on parameters.
In MaxlikMT, the same procedure computing the log-likelihood or objective function will be used to compute analytical derivatives as well if they are being provided. Its return argument is a maxlikmtResults structure with three members, a scalar, or Nx1 vector containing the log-likelihood (or objective), a 1xK vector, or NxK matrix of first derivatives, and a KxK matrix or NxKxK array of second derivatives (it needs to be an array if the log-likelihood is weighted).
Of course the derivatives are optional, or even partially optional, i.e., you can compute a subset of the derivatives if you like and the remaining will be computed numerically. This procedure will have an additional argument which tells the function which to compute, the log-likelihood or objective, the first derivatives, or the second derivatives, or all three. This means that calculations in common will not have to be redone.
Platform: Windows, Mac and Linux.
Requirements: GAUSS/GAUSS Light v10 or higher; Linux requires v10.0.4 or higher.