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I have an ordinary least squares setup y = Ac where A is an NxM (N>>M) matrix, c the unknown coefficients and y the measurements.

Now WEIGHTED least squares allows to weight the MEASUREMENTS if, for example, some measurements are more important or contain a lower variance.

However, I am looking for a solution of putting weights on the coefficient vector. Pictorially speaking, some values in my coefficient vector c are more important than others and I would like emphasize some more than others using my limited set of N measurements.

Just adding a diagonal weighting matrix w as follows does not work:

[tex]

\min_c \| y - Awc \|_2

[/tex]

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# Weighted Least Squares for coefficients

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