VARMA._max_supported_lags#

VARMA._max_supported_lags()[source]#

Largest autoregressive order the sample can identify.

Return type:

int

Returns:

The order at which the design would still have more rows than columns once the deterministic terms and the k * q innovation columns are counted.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> VARMA(rng.standard_normal((400, 2)), order=(1, 1))._max_supported_lags()
132