Re: Contribution to the optimization toolbox

[Michael Creel]

Thanks for the new version. Note that when dim is increased, bfgsmin
need to have max iters increased, otherwise it chokes before
converging. Setting control={10000,0} with dim=100, I get the results

octave:4> compare
100/100
Results using analytic gradient
ans =

   3.1157e-01   4.6628e-08   1.2482e-15   4.3526e-01   6.0199e-02   1.6613e-03

ans =

   2.9021e-01   2.9620e-08   3.5626e-16   4.3474e-01   4.5174e-02   5.0746e-04

so bfgsmin is finding the correct answer.


When dim is high, it makes sense to try lbfgs. Setting
control={10000,0,1,1,5} to use a memory of 5 iterations, the results
for dim=100 are

octave:6> compare
100/100
Results using analytic gradient
ans =

   9.0097e-02   1.1931e-06   1.6012e-12   4.3407e-01   5.7046e-02   1.5292e-03

ans =

   8.7479e-02   3.4221e-07   4.5890e-14   4.3370e-01   3.7205e-02   3.5980e-04

so lbfgs is considerably faster than bfgs.

For setting up a bank of test problems, do you think that this test
script captures the important metrics: speed and accuracy? Anything
else to add? I may take the project on,

Cheers, M.