statsmodels.tsa.vector_ar.irf.IRAnalysis.plot¶

IRAnalysis.plot(orth=False, *, impulse=None, response=None, signif=0.05, plot_params=None, figsize=(10, 10), 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 : {str, int}¶

variable providing the impulse

response : {str, 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¶

figsize : (float, float), default (10, 10)¶

Figure size (width, height in inches)

plot_stderr : bool, default True¶

Plot standard impulse response error bands

stderr_type : str¶

‘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¶