Re: QR vs LU factorisation

[Jaroslav Hajek]

On Mon, Jun 30, 2008 at 11:31 PM, Vic Norton <address@hidden> wrote:
>
> On Jun 30, 2008, at 5:16 PM, Jaroslav Hajek wrote:
>
>>> SVD is the best solution in this case. For example, to
>>> invert a matrix A choose an svd "precision", say
>>>
>>>   svdcut = 1e-12;
>>>
>>> Then do
>>>
>>>   [U S V] = svd(A, 1);
>>>   sig = diag(S);
>>>   rnk = 0;
>>>   for i = 1 : length(sig)
>>>      if sig(i)/sig(1) < svdcut; break; endif
>>>      rnk++;
>>>   endfor
>>>   Ainv = ( V(:, 1:rnk) * diag(1 ./ sig(1:rnk)) ) * U(:, 1:rnk)';
>>>
>>> to get the (pseudo)inverse of A.
>>
>>
>> or just use "pinv".
>
> What is the "precision" of "pinv"? If your data only is accurate to 6
> digits, why try for anything more accurate than svdcut = 1e-7 would produce?
> Any additional "accuracy" is pure noise.
>

OK, that's what the second argument (TOL) is for. It's true, however,
that it would perhaps be more useful to specify a relative rather than
absolute threshold.

> Regards,
>
> Vic
>



-- 
RNDr. Jaroslav Hajek
computing expert
Aeronautical Research and Test Institute (VZLU)
Prague, Czech Republic
url: www.highegg.matfyz.cz