SpectralDensityResult.periods#

SpectralDensityResult.periods()[source]#

Each grid frequency as a period, in observations per cycle.

\(2\pi / \omega\), with frequency zero mapping to infinity: for quarterly data the business-cycle band of 6 to 32 quarters is frequencies \(2\pi / 32\) to \(2\pi / 6\).

Return type:

NDArray[double]

Returns:

A (n,) array, inf first and 2.0 last.

Example

>>> import numpy as np
>>> from cultivars.multivariate.reduced_form.vector_autoregression import VAR
>>> y = np.random.default_rng(0).standard_normal((200, 2))
>>> density = SpectralDensity(VAR(y, order=1).fit(), n_frequencies=5).compute()
>>> density.periods().round(2).tolist()
[inf, 8.0, 4.0, 2.67, 2.0]