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"reduced" corrected to "rank-revealingly"; link added
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Alex Becker
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The Moore-Penrose pseudoinverse is probably what you're looking for. The pseudoinverse solution $A^+b$ is the smallest norm $x$ such that $\|Ax-b\|_2$ is minimized. It can be computed using QR decomposition (see here), although you have to use reducedrank-revealing QR when $A$ does not have full column rank. A more complete explanation is given here.

The Moore-Penrose pseudoinverse is probably what you're looking for. The pseudoinverse solution $A^+b$ is the smallest norm $x$ such that $\|Ax-b\|_2$ is minimized. It can be computed using QR decomposition (see here), although you have to use reduced QR when $A$ does not have full column rank.

The Moore-Penrose pseudoinverse is probably what you're looking for. The pseudoinverse solution $A^+b$ is the smallest norm $x$ such that $\|Ax-b\|_2$ is minimized. It can be computed using QR decomposition although you have to use rank-revealing QR when $A$ does not have full column rank. A more complete explanation is given here.

Source Link
Alex Becker
  • 881
  • 5
  • 13

The Moore-Penrose pseudoinverse is probably what you're looking for. The pseudoinverse solution $A^+b$ is the smallest norm $x$ such that $\|Ax-b\|_2$ is minimized. It can be computed using QR decomposition (see here), although you have to use reduced QR when $A$ does not have full column rank.