code: import numpy as np
  import statsmodels.api as sm
  import pandas as pd
  
  mdatagen = sm.datasets.macrodata.load().data
  mdata = mdatagen[['realgdp','realcons','realinv']]
  names = mdata.dtype.names
  start = pd.datetime(1959, 3, 31)
  end = pd.datetime(2009, 9, 30)
  #qtr = pd.DatetimeIndex(start=start, end=end, freq=pd.datetools.BQuarterEnd())
  qtr = pd.DatetimeIndex(start=start, end=end, freq='BQ-MAR')
  data = pd.DataFrame(mdata, index=qtr)
  data = (np.log(data)).diff().dropna()
  
  #define structural inputs
  A = np.asarray([[1, 0, 0],['E', 1, 0],['E', 'E', 1]])
  B = np.asarray([['E', 0, 0], [0, 'E', 0], [0, 0, 'E']])
  A_guess = np.asarray([0.5, 0.25, -0.38])
  B_guess = np.asarray([0.5, 0.1, 0.05])
  mymodel = SVAR(data, svar_type='AB', A=A, B=B, freq='Q')
  res = mymodel.fit(maxlags=3, maxiter=10000, maxfun=10000, solver='bfgs')
  res.irf(periods=30).plot(impulse='realgdp', plot_stderr=True,
                           stderr_type='mc', repl=100)
  
apis: pandas.DatetimeIndex pandas.datetime pandas.DataFrame numpy.asarray numpy.log