class_docstr: obsolete VAR class, use tsa.VAR instead, for internal use only
  
  
  Examples
  --------
  
  >>> v = Var(ar2s)
  >>> v.fit(1)
  >>> v.arhat
  array([[[ 1.        ,  0.        ],
          [ 0.        ,  1.        ]],
  
         [[-0.77784898,  0.01726193],
          [ 0.10733009, -0.78665335]]])
class_docstr_tok: ["obsolete","VAR","class",",","use","tsa.VAR","instead",",","for","internal","use","only","Examples","--","--","--","--",">",">",">","v","=","Var","(","ar2s",")",">",">",">","v.fit","(","1",")",">",">",">","v.arhat","array","(","[","[","[","1.",",","0",".","]",",","[","0.",",","1",".","]","]",",","[","[","-0.77784898",",","0.01726193","]",",","[","0.10733009",",","-0.78665335","]","]","]",")"]
code: def __init__(self, y):
      self.y = y
      self.nobs, self.nvars = y.shape
  
imports: import numpy
  from scipy import signal
  from statsmodels.tsa.tsatools import lagmat
label_desc: Use image node_id 1 to create a new _Var object  with example: obj = _Var(y)