IRAnalysis.plot()

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 :