pyacs.glinalg.solve.lscov module

pyacs.glinalg.solve.lscov.lscov(G, d, cov, method='chol')[source]

Solve the least-squares problem with data covariance matrix.

Parameters:

  • G (ndarray) – m x n model matrix (2D).

  • d (ndarray) – m observation vector (1D).

  • cov (ndarray) – m x m covariance matrix for d.

  • method (str, optional) – ‘chol’ for Cholesky (default).

Returns:

Solution (same as ls on whitened system).

Return type:

ndarray