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| regression optimization [message #71395] |
Thu, 17 June 2010 00:35 |
Klemen
Messages: 80
Registered: July 2009
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Member |
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Hello all,
I have a variable to be explained with 12 attributes (at the moment
all of them being arrays of 300 by 100, but in the future it can be
even larger than 1000 by 1000 array). I would like to preform a moving
window analysis. For each window I want to estimate the optimal
multiple linear regression parameters.
Optimal means that it is not necessary that all of 12 variables are
used (some of them are correlated). So I want to get out an equation
that has 2,3,4... parameters and provide the best statistics.
The problem is also that not all the values within a moving window can
be used - some pixels contain no data. Defining NaN for these values
and using the code similar to the one written by Bringfried Stecklum
( http://groups.google.com/group/comp.lang.idl-pvwave/browse_t hread/
thread/17613c70b78f1ac4/6891d260db6c7c93?
lnk=gst&q=regression#6891d260db6c7c93), I can test which of attributes
might be significant for the regression.
The question is, how to proceed. From those attributes that I know
that they are correlated among each other, I want to use just the one
that explains the most variability. I can somehow imagine to select
the final 2-4 attributes that should be used for multiple regression
without using any FOR loops. But how do I do the final step -
estimation of multiple regression parameters without using any loops?
Any idea?
Thank you!
Klemen
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