And I assume that you mean here the gradient and jacobians are the same though in theory gradients are subsets of jacobian. I think if I append the dh and dg (measured in line 356 and 357 for nonlinear case); I will get the Jacobian matrix.
On Fri, Aug 30, 2019 at 11:17 AM Jubeyer Rahman <[email protected]> wrote: > Well I am referring to line 390 and 392 in mips.m. > > Regards, > Jubeyer > > On Fri, Aug 30, 2019 at 10:58 AM Ray Zimmerman <[email protected]> wrote: > >> The mips() function requires that you pass in function handles for >> functions that evaluate the objective and it’s gradient (f_fcn), and the >> constraints and their gradients (gh_fcn) or Jacobian, and Hessian ( >> hess_fcn). So, mips itself does not compute these quantities (e.g. via >> finite differences), but it uses the functions it is provided. >> >> Regarding the transpose matrices, I’m not sure where you are referring to >> (maybe provide a specific file and line number), but MIPS was designed to >> be as compatible as possible with the way derivative and Hessian functions >> were defined for fmincon (part of MATLAB’s Optimization Toolbox) and I >> believe that required a transpose somewhere. >> >> Best, >> >> Ray >> >> >> >> >> On Aug 29, 2019, at 4:55 PM, Jubeyer Rahman <[email protected]> wrote: >> >> Hi, >> Is there any Jacobian calculation taking place in mips.m? If not, what >> function can I use to calculate the Jacobian matrix inside the mips where >> Lxx is calculated (hessian)? >> >> Another question is, while taking the derivative to produce Lx from L ; >> why the transpose matrices become regular, say for example, lam' becomes >> lam, etc.? >> >> -Jubeyer >> >> >>
