class_docstr: Base class for plotting and computing IRF-related statistics, want to be
  able to handle known and estimated processes
class_docstr_tok: ["Base","class","for","plotting","and","computing","IRF-related","statistics",",","want","to","be","able","to","handle","known","and","estimated","processes"]
docstr: Plot cumulative impulse response functions
  
  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 standard errors
  seed : int
      np.random.seed for Monte Carlo replications
docstr_tok: ["Plot","cumulative","impulse","response","functions","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","standard","errors","seed",":","int","np.random.seed","for","Monte","Carlo","replications"]
code: def plot_cum_effects(
      self,
      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,
  ):
      """
      Plot cumulative impulse response functions
  
      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 standard errors
      seed : int
          np.random.seed for Monte Carlo replications
      """
  
      if orth:
          title = "Cumulative responses responses (orthogonalized)"
          cum_effects = self.orth_cum_effects
          lr_effects = self.orth_lr_effects
      else:
          title = "Cumulative responses"
          cum_effects = self.cum_effects
          lr_effects = self.lr_effects
  
      if stderr_type not in ["asym", "mc"]:
          raise ValueError("`stderr_type` must be one of 'asym', 'mc'")
      else:
          if stderr_type == "asym":
              stderr = self.cum_effect_cov(orth=orth)
          if stderr_type == "mc":
              stderr = self.cum_errband_mc(
                  orth=orth, repl=repl, signif=signif, seed=seed
              )
      if not plot_stderr:
          stderr = None
  
      fig = plotting.irf_grid_plot(
          cum_effects,
          stderr,
          impulse,
          response,
          self.model.names,
          title,
          signif=signif,
          hlines=lr_effects,
          subplot_params=subplot_params,
          plot_params=plot_params,
          figsize=figsize,
          stderr_type=stderr_type,
      )
      return fig
  
imports: import numpy
  import numpy.linalg
  import scipy.linalg
  from statsmodels.tools.decorators import cache_readonly
  import statsmodels.tsa.tsatools
  import statsmodels.tsa.vector_ar.plotting
  import statsmodels.tsa.vector_ar.util
label_desc: Use image node_id 6 for calling the BaseIRAnalysis obj's underlying member method code with example usage: obj.plot_cum_effects(orth) and returns: fig