[Numpy-discussion] Identifying Colinear Columns of a Matrix
Charles R Harris
Fri Aug 26 13:57:26 CDT 2011
On Fri, Aug 26, 2011 at 12:38 PM, Mark Janikas <email@example.com> wrote:
> Charles! That looks like it could be a winner! It looks like you always
> choose the last column of the U matrix and ID the columns that have the same
> values? It works when I add extra columns as well! BTW, sorry for my lack
> of knowledge… but what was the point of the dot multiply at the end? That
> they add up to essentially zero, indicating singularity? Thanks so much!
The indicator of collinearity is the singular value in d, the corresponding
column in u represent the linear combination of rows that are ~0, the
corresponding row in v represents the linear combination of columns that are
~0. If you have several combinations that are ~0, of course you can add them
together and get another. Basically, if you take the rows in v corresponding
to small singular values, you get a basis for the for the null space of the
matrix, the corresponding columns in u are a basis for the orthogonal
complement of the range of the matrix. If that is getting a bit technical
you can just play around with things.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion