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From Mauro Talevi <mauro.tal...@aquilonia.org>
Subject Re: [math] Improving numerics in OLSMultipleLinearRegression
Date Fri, 20 Jun 2008 11:15:00 GMT
Phil,

Phil Steitz wrote:
> I think R uses QR as described above.  Comments or suggestions for other 
> default implementations are most welcome.  We should aim to provide a 
> default implementation that is reasonably fast and provides good 
> numerics across a broad range of design matrices.

Got around to testing QR decomposition on OLS.

The short answer is that is does not seems to make much difference. 
Rather it looks like the dataset and the number of observations that are 
far more significant for good numerics, as is also shown by your recent 
addition of Swiss Fertility dataset (with nobs 3 times as large), for 
which results match (either with or without QR) up to 10^-12 tolerance.

Here's the resulting numerics for comparison:

Longley dataset (nobs=16):

PL=[-3482258.6569276676, 15.06187677821299, -0.03581918037047249, 
-2.0202298136474104, -1.0332268695603801, -0.051104103746114404, 
1829.1514737363977]
QR=[-3482258.7119702557, 15.061873615257795, -0.03581918168712586, 
-2.020229840231328, -1.0332268778552742, -0.05110409751647271, 
1829.1515061042903]
LG=[-3482258.63459582, 15.0618722713733, -0.035819179292591, 
-2.02022980381683, -1.03322686717359, -0.0511041056535807, 1829.15146461355]

Swiss Fertility dataset (nobs=47):

PL=[91.05542390271336, -0.22064551045713723, -0.26058239824327045, 
-0.9616123845602972, 0.12441843147162471]
QR=[91.05542390271366, -0.22064551045714642, -0.26058239824326457, 
-0.9616123845602974, 0.12441843147162669]
SF=[91.05542390271397, -0.22064551045715, -0.26058239824328, 
-0.9616123845603, 0.12441843147162]

(Legend: PL = plain OLS, QR = QR-decomposed OLS, LG = Longley R results, 
SF = Swiss Fertility R results).

Interestingly, it's only on the intercepts (ie the first regression 
parameter) that we get the very poor numerics.  While not a numerical 
argument, one could say that the statistically more significant 
parameter is the slope.

Anyway, attached is patch with QR-based implementation and modified test 
to print out comparison results.

Cheers



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