Filtering data from numerical minimization
- To: mathgroup at smc.vnet.net
- Subject: [mg116185] Filtering data from numerical minimization
- From: Sebastian <sebhofer at gmail.com>
- Date: Fri, 4 Feb 2011 01:40:37 -0500 (EST)
I have a function f(n,x,y,z) that I want to numerically minimize with
respect to x,y,z for a list of n=1...N. The function is pretty
complicated and also contains other parameters, which are fixed as far
as optimization is concerned. I use NMinimize to create a table for
different values of n. This effectively leaves me with 4 lists (f_min,
x_min,...), where f_min = f(x_min, y_min, z_min). I then plot these
lists against the vector n.
Depending on the other parameters the minimization sometimes works
well, and sometimes it doesn't. The problem is the following: while
the overall form of the curves is often easily recognizable by eye,
there is some noise on top of it, i.e. some of the points (every 5th
say) are just way off. As I don't think that f behaves that way, but
rather NMinimize fails to find the correct value, I'd like to filter
that noise. Filtering the points by hand, however, doesn't seem like a
feasible solution. Does anyone know a good way to tackle this problem?
I already tried running MovingMedian which works reasonably well but
I'd like to keep the rest of the data untouched if possible.
I'm happy for all suggestions!
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