function spd_inv

deeptime.numeric.spd_inv(W, epsilon=1e-10, method='QR')

Compute matrix inverse of symmetric positive-definite matrix \(W\).

by first reducing W to a low-rank approximation that is truly spd (Moore-Penrose inverse).

Parameters:

• W (ndarray((m,m), dtype=float)) – Symmetric positive-definite (spd) matrix.

• epsilon (float) – Truncation parameter. Eigenvalues with norms smaller than this cutoff will be removed.

• method (str) –

  Method to perform the decomposition of \(W\) before inverting. Options are:

  • ’QR’: QR-based robust eigenvalue decomposition of W

  • ’schur’: Schur decomposition of W

Returns:

L – the Moore-Penrose inverse of the symmetric positive-definite matrix \(W\)

Return type:

ndarray((n, r))