[SciPy-user] Least squares with covariance - equivalent to Matlab [x, stdx, mse] = lscov(A, b, V)

[Eleanor]

Hi 

I'm fairly new to python and Scipy.

I need to solve overdeteremined least squares A * x = b with b having a known
covariance matrix V.

I've previously used Matlab's lscov function

http://www.mathworks.com/access/helpdesk/help/techdoc/ref/lscov.html

and as a learning exercise, I wrote a low level version of this using the
cholesky, qr, solve, svd functions from scipy.linalg. (I had a peek at lscov.m
for help).

My question is:
Can I do this more directly with an existing scipy function?

cheers Eleanor