class_docstr: Impulse response analysis class. Computes impulse responses, asymptotic
  standard errors, and produces relevant plots
  
  Parameters
  ----------
  model : VAR instance
  
  Notes
  -----
  Using Lütkepohl (2005) notation
class_docstr_tok: ["Impulse","response","analysis","class",".","Computes","impulse","responses",",","asymptotic","standard","errors",",","and","produces","relevant","plots","Parameters","--","--","--","--","--","model",":","VAR","instance","Notes","--","--","-","Using","L\u00fctkepohl","(","2005",")","notation"]
code: def __init__(
      self,
      model,
      P=None,
      periods=10,
      order=None,
      svar=False,
      vecm=False,
  ):
      BaseIRAnalysis.__init__(
          self,
          model,
          P=P,
          periods=periods,
          order=order,
          svar=svar,
          vecm=vecm,
      )
  
      if vecm:
          self.cov_a = model.cov_var_repr
      else:
          self.cov_a = model._cov_alpha
      self.cov_sig = model._cov_sigma
  
      # memoize dict for G matrix function
      self._g_memo = {}
  
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 1 to create a new IRAnalysis object from inherited base classes: BaseIRAnalysis with example: obj = IRAnalysis(model, P, periods, order, svar, vecm)