[SciPy-User] linalg question:cholesky for semidefinite, or LDL, QR equivalent for squared matrix
josef.pktd at gmail.com
josef.pktd at gmail.com
Wed Apr 29 14:35:29 EDT 2015
https://github.com/numpy/numpy/pull/4079
I'm looking for the equivalent of Cholesky for possibly singular, symmetric
matrices using numpy or scipy linalg.
details:
I'm writing a function that can either take the data x (nobs, k_vars) or
the moment matrix x.T.dot(x) (k_vars, k_vars), and I want to get the same
result in both cases.
Given data x, all I need is the R of the QR decomposition.
If the moment matrix is not singular, then I can get the same with the
Cholesky decomposition.
However, what's the equivalent of R in QR if x is not of full rank and the
moment matrix is singular?
QR on the moment matrix gives different numbers and I don't know how to
recover the correct R.
requirement: I need the same sequential decomposition as qr and cholesky to
be used for sequential least squares.
Thanks,
Josef
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