QVARResult.coefficients#

QVARResult.coefficients(quantile)[source]#

One level’s lag stack A_1(tau), ..., A_p(tau).

Parameters:

quantile (float) – An estimated level.

Return type:

NDArray[double]

Returns:

A (p, k, k) stack; [l - 1, i, j] is the coefficient on lag l of variable j in the tau-quantile equation of variable i.

Raises:

SpecificationError – If the level was not estimated.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> y = np.zeros((300, 2))
>>> for t in range(1, 300):
...     y[t] = 0.5 * y[t - 1] + rng.standard_normal(2)
>>> res = QVAR(y, order=1).fit(quantiles=(0.25, 0.5, 0.75))
>>> res.coefficients(0.5).shape
(1, 2, 2)
>>> bool(np.all(np.abs(np.diag(res.coefficients(0.5)[0]) - 0.5) < 0.15))
True
>>> bool(np.allclose(res.coefficients(0.75), res.coefficient_stacks[2]))
True