NSSDNResult.power_share

property NSSDNResult.power_share: NDArray[float64]

(k,) each component’s share of mean contribution power over the sample.

\[\pi_k = \frac{\overline{\tilde A_{\cdot,k}^2}} {\sum_{j=1}^{K} \overline{\tilde A_{\cdot,j}^2}}, \qquad \overline{\tilde A_{\cdot,k}^2} = \frac{1}{r}\sum_{t} \tilde A_{t,k}^2,\]

with \(\tilde A\) the effective_amplitude. The shares sum to one and are the power share column of the summary table.

Example

>>> import numpy as np
>>> y = np.sin(0.2 * np.arange(120.0))
>>> res = NSSDN(y, k=3, state_dim=8, schedule=(Stage(1e-2, 20),), seed=0).fit()
>>> res.power_share.shape, bool(np.isclose(res.power_share.sum(), 1.0))
((3,), True)