Using QR decomposition to solve least squares in Matlab -

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i using matlab estimate regression model ordinary least squares (ols).

the model y = xb, x sparse matrix dimension 500000 x 2500. i'm using qr decomposition:

[c,r] = qr(x,y,0)

and estimating b with

b = r\c

my question whether need worried numerical errors here. there additional iteration need do? should check condition number of r, or r'r? guidance appreciated.

the matlab recommended way is:

b = x\y;

check http://www.mathworks.com/help/matlab/ref/mldivide.html , section more about in particular, see how matlab handles different cases under hood.

if want exploit sparseness of x declare x sparse, x = sparse(x), before call \.


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