pyacs.gts.lib.gts_estimators module

pyacs.gts.lib.gts_estimators.least_square(A, L, P=None)[source]

Least-squares estimation for AX + L = 0 with optional weight matrix P.

Parameters:

  • A (ndarray) – Design matrix.

  • L (ndarray) – Observation vector.

  • P (ndarray, optional) – Weight matrix for L (default identity).

Returns:

X (unknowns), s_X (parameter std), V (residuals), s_V (residual std), std (sigma_0), S (model A*X).

Return type:

tuple

Raises:

ValueError – If N is singular or has negative diagonal in Q.