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)