"Mike " <michael.gerstREMOVE@yale.edu> wrote in message <email@example.com>... > Hi all, > > I have setup a minimization problem using fmincon with > linear and non linear inequality constraints. I am having > the problem where fmincon will guess negative values for > some of the decision variables, even though I have included > a zero lower bound in the constraint matrix (instead of > using "lb"). > > After looking through the results in more detail, this > appears to happen when certain variables have been minimized > to zero. In order to further decrease the value of the > objective function, fmincon will try to assign a negative > value to some of the decision variables which are already at > zero. Also, this usually happens when the objective > function is nearing a minimum. > > Why is this happening when I have coded in a lower bound of > zero? Are there any ways to prevent this from happening? > Any help would be greatly appreciated, as this has turned > out to be a very frustrating problem. > > Thanks, > Mike
Hi Mike, making sure that parameters are positive during estimation is a quite common problem. Instead of using the bounded estimation method, I usually find it simpler to estimate the square of the parameter. For example, if I have a parameter b that should be at least zero, I use b^2 as a parameter in the estimation, and insert the estimated parameter a = b^2 into the model as sqrt(a). That should make the estimation routine to never assign a negative value to your parameter.