Here are a couple of quick references, from the R docs and Google
 
http://www.netlib.org/lapack/lug/node69.html  (QR decomp)
http://www.mathcs.duq.edu/larget/math496/qr.html (QR decomp and regression)
 
The problem with numerics is that accuracy tests can only show problems -- 
i.e., if you find an example that shows your algorithm performing poorly, you 
know you have a problem; but if all of your test cases show good accuracy that 
does not mean the algorithm is numerically sound.  That's why numerical 
analysis exists and why what we tend to do in [math] is to look at the relevant 
numerical analysis literature (in this case numerical linear algebra) and what 
other packages do when choosing an algorithm.  Then, since another wonderful 
feature of numerics is that it is almost always true that there is not one 
"best" algorithm for all cases, we try to make the implementation pluggable.
 
I agree with Kim that we can probably grab the QR decomp algorithm from JAMA 
(have not looked recently, but I vaguely recall it being there).  I will work 
on making sure that this does not present any copyright problems.  Any 
suggestions / straw men for what the interface should look like?
 
Phil

        -----Original Message----- 
        From: Tzvika Barenholz [mailto:[EMAIL PROTECTED] 
        Sent: Mon 1/10/2005 9:34 AM 
        To: Jakarta Commons Developers List 
        Cc: 
        Subject: Re: [commons - math] Vector and Scalar multiplications
        
        

        > The formulas that you cite look correct mathematically, but
        > unfortunately not the best numerically. The reference in the post 
above
        > describes a better computational approach.  Patches to support QR
        > decomposition of real matrices so we can implement that algorithm or
        > other numerically sound multiple regression approaches would be 
appreciated.
        >
        > Phil
        
        
        not to sound too dumb, but does anyone have a good reference on what
        this QR decomposition actually is? I'd love to look at it.
        
        By the way, i've written some tests for my own RealMatrix-based
        implementation of multiple linear regression, and the numerics aren't
        too bad at all as far as i could tell (first differences appearing
        around the 12th digit after the decimal point or so). that is, without
        a more comprehensive test.  Do you guys maybe have a requirement for
        how accurate an algorithm must be to be acceptable?
        
        ---------------------------------------------------------------------
        To unsubscribe, e-mail: [EMAIL PROTECTED]
        For additional commands, e-mail: [EMAIL PROTECTED]
        
        

Reply via email to