statsmodels.tsa.vector_ar.var_model.VARResults.irf_resim#

VARResults.irf_resim(orth=False, repl=1000, steps=10, rng=None, burn=100, cum=False)[source]#

Simulates impulse response function, returning an array of simulations.

Used for Sims-Zha ([SimsZha1999]) error band calculation.

Parameters:
orthbool, optional

Compute orthogonalized impulse response error bands. The default is False.

replint, optional

number of Monte Carlo replications to perform. The default is 1000.

stepsint, optional

number of impulse response periods. The default is 10.

rngint, array_like of int, numpy.random.Generator, or numpy.random.RandomState, optional

Source of random numbers used for the Monte Carlo replications. If rng is None, a new Generator is created using fresh entropy from the operating system. If rng is an int, a new RandomState instance is created, seeded with rng; this integer-seeding behavior is deprecated and will change to creating a Generator in a future release. If rng is already a Generator or RandomState instance, that instance is used.

seedint, array_like of int, numpy.random.Generator, or numpy.random.RandomState, optional

Deprecated since version 0.15: seed has been deprecated. In-line with SPEC-007, use rng for passing a random number generator or seed.

burnint, optional

number of initial observations to discard for simulation. The default is 100.

cumbool, optional

produce cumulative irf error bands. The default is False.

Returns:
ndarray

Array of simulated impulse response functions.

Notes

[SimsZha1999]

Sims, Christoper A., and Tao Zha. 1999. “Error Bands for Impulse Responses”. Econometrica 67: 1113-1155.