statsmodels.tsa.vector_ar.irf.IRAnalysis.plot

IRAnalysis.plot(orth=False, impulse=None, response=None, signif=0.05, plot_params=None, subplot_params=None, plot_stderr=True, stderr_type='asym', repl=1000, seed=None, component=None)

Plot impulse responses

Parameters:

orth : bool, default False

Compute orthogonalized impulse responses

impulse : string or int

variable providing the impulse

response : string or int

variable affected by the impulse

signif : float (0 < signif < 1)

Significance level for error bars, defaults to 95% CI

subplot_params : dict

To pass to subplot plotting funcions. Example: if fonts are too big, pass {‘fontsize’ : 8} or some number to your taste.

plot_params : dict

plot_stderr: bool, default True

Plot standard impulse response error bands

stderr_type: string

‘asym’: default, computes asymptotic standard errors ‘mc’: monte carlo standard errors (use rpl)

repl: int, default 1000

Number of replications for Monte Carlo and Sims-Zha standard errors

seed: int

np.random.seed for Monte Carlo replications

component: array or vector of principal component indices