Does least squares solution to Ax=b depend on choice of norm

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SUMMARY

The least squares solution to the equation Ax=b, represented as \(\hat{x}=(A^TA)^{-1}A^T\mathbb{b}\), is fundamentally based on the standard Euclidean distance. This solution does not vary with the choice of distance function, as it assumes the standard scalar product and its induced norm. While alternative distance measures may yield different results, they typically do not provide explicit solutions and often require numerical methods for computation.

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kaxzr
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To find the closest point to [itex]b[/itex] in the space spanned by the columns of [itex]A[/itex] we have:
[tex]\mathbb{\hat{x}}=(A^TA)^{-1}A^T\mathbb{b}[/tex]
My question is, shouldn't this solution ##\hat{x}## depend on the choice of distance function over the vector space? Choosing two different distance functions might give two different ##\hat{x}##s. But this equation does not make any reference to the choice of distance function.

Can anyone explain this to me? This is not directly a homework question but I am just trying to get a better understanding of the concepts here.

Thanks.
 
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If nothing else is given, use the standard scalar product and its induced norm.
 
kaxzr said:
To find the closest point to [itex]b[/itex] in the space spanned by the columns of [itex]A[/itex] we have:
[tex]\mathbb{\hat{x}}=(A^TA)^{-1}A^T\mathbb{b}[/tex]
My question is, shouldn't this solution ##\hat{x}## depend on the choice of distance function over the vector space? Choosing two different distance functions might give two different ##\hat{x}##s. But this equation does not make any reference to the choice of distance function.

Can anyone explain this to me? This is not directly a homework question but I am just trying to get a better understanding of the concepts here.

Thanks.

This function is *assuming* standard Euclidean distance. Of course for other measures of distance you will get different results. Some other norms do not lead to explicit solutions, but are only doable numerically.
 

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