pyacs.lib.glinalg.lsw_full

Solve weighted least-squares and return solution and posterior covariance.

pyacs.lib.glinalg.lsw_full.lsw_full(G, d, std, verbose=False)

Solve weighted least-squares and return solution and posterior covariance.

Parameters:

• G (numpy.ndarray) – m x n design matrix.

• d (numpy.ndarray) – m observation vector.

• std (array_like) – Standard deviations for d (length m).

• verbose (bool, optional) – If True, print lapack info. Default is False.

Returns:

• X (numpy.ndarray) – Solution vector.

• COV (numpy.ndarray) – Posterior covariance of the solution.

• V (numpy.ndarray) – Residuals d - G*X.