matlab - using singular value decomposition (svd) in quadratic regression -


in order quadratic regression on rather large data set solve following equation using svd(singular value decomposition): b(nx1)=a(nx3)*x(3x1) thinking use matlab that, tips? goal compute matrix x

it seems call quadratic regression minimal square error regression. in case computation easy:

1) multiply both left sides a'(3xn) arriving to

a'(3xn)b(nx1) = a'(3xn)a(nx3) x(3x1)

2) multiply both left sides inverse of a'(nx1) a(nx3) arriving to

inv(a'(3xn)a(nx3))a'(3xn)b(nx1) = x(3x1)

3) use svd evaluate inverse above, see most efficient matrix inversion in matlab

see minimizing error of formula in matlab (least squares?)


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