class_docstr: class to keep track of Varma polynomial format
  
  
  Examples
  --------
  
  ar23 = np.array([[[ 1. ,  0. ],
                   [ 0. ,  1. ]],
  
                  [[-0.6,  0. ],
                   [ 0.2, -0.6]],
  
                  [[-0.1,  0. ],
                   [ 0.1, -0.1]]])
  
  ma22 = np.array([[[ 1. ,  0. ],
                   [ 0. ,  1. ]],
  
                  [[ 0.4,  0. ],
                   [ 0.2, 0.3]]])
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docstr: stack ar and lagpolynomial vertically in 2d array
  
  this is the Kalman Filter representation, I think
docstr_tok: ["stack","ar","and","lagpolynomial","vertically","in","2d","array","this","is","the","Kalman","Filter","representation",",","I","think"]
code: def hstackarma_minus1(self):
      """stack ar and lagpolynomial vertically in 2d array
  
      this is the Kalman Filter representation, I think
      """
      a = np.concatenate((self.ar[1:], self.ma[1:]), 0)
      return a.swapaxes(1, 2).reshape(-1, self.nvarall)
  
imports: import numpy
  from scipy import signal
  from statsmodels.tsa.tsatools import lagmat
label_desc: Use image node_id 6 for calling the VarmaPoly obj's underlying member method code with example usage: obj.hstackarma_minus1() and returns: a