Prev: Strange Filter Behavior?
Next: rescaling for fmincon
From: Matt J on 27 Jul 2010 17:48
"Samuel Edwards" <DJeter1234(a)AOL.com> wrote in message <i2nauv$bfo$1(a)fred.mathworks.com>...
> I am running a least squares minimization with fmincon to solve a least squares problem. Essentially, a 5-tuple of parameters maps to an 8-tuple of percentages. The parameters are of the form (mean, 1/variance1, 1/variance2, 1/variance3, constant scaled to mean). Unfortunately, it seems that the sum of squares function is very flat around the minimum over a pretty big range of variance1,2,3 and constant.
========

In addition to my last point, is there a reason that you are parametrizing using
1/variance instead of the variance, or better yet the standard deviation, itself? By taking 1/x, you are diminishing the sensitivity of the objective function to variations in x when x is large. This could easily contribute to scaling problems.
 | 
Pages: 1
Prev: Strange Filter Behavior?
Next: rescaling for fmincon