class_docstr: Class represents a known SVAR(p) process
  
  Parameters
  ----------
  coefs : ndarray (p x k x k)
  intercept : ndarray (length k)
  sigma_u : ndarray (k x k)
  names : sequence (length k)
  A : neqs x neqs np.ndarray with unknown parameters marked with 'E'
  A_mask : neqs x neqs mask array with known parameters masked
  B : neqs x neqs np.ndarry with unknown parameters marked with 'E'
  B_mask : neqs x neqs mask array with known parameters masked
class_docstr_tok: ["Class","represents","a","known","SVAR","(","p",")","process","Parameters","--","--","--","--","--","coefs",":","ndarray","(","p","x","k","x","k",")","intercept",":","ndarray","(","length","k",")","sigma_u",":","ndarray","(","k","x","k",")","names",":","sequence","(","length","k",")","A",":","neqs","x","neqs","np.ndarray","with","unknown","parameters","marked","with","'","E'","A_mask",":","neqs","x","neqs","mask","array","with","known","parameters","masked","B",":","neqs","x","neqs","np.ndarry","with","unknown","parameters","marked","with","'","E'","B_mask",":","neqs","x","neqs","mask","array","with","known","parameters","masked"]
docstr: Compute Structural MA coefficient matrices using MLE
  of A, B
docstr_tok: ["Compute","Structural","MA","coefficient","matrices","using","MLE","of","A",",","B"]
code: def svar_ma_rep(self, maxn=10, P=None):
      """
  
      Compute Structural MA coefficient matrices using MLE
      of A, B
      """
      if P is None:
          A_solve = self.A_solve
          B_solve = self.B_solve
          P = np.dot(npl.inv(A_solve), B_solve)
  
      ma_mats = self.ma_rep(maxn=maxn)
      return np.array([np.dot(coefs, P) for coefs in ma_mats])
  
imports: import numpy
  import numpy.linalg
  from numpy.linalg import slogdet
  from statsmodels.tools.decorators import deprecated_alias
  from statsmodels.tools.numdiff import approx_fprime, approx_hess
  import statsmodels.tsa.base.tsa_model
  from statsmodels.tsa.vector_ar.irf import IRAnalysis
  import statsmodels.tsa.vector_ar.util
  from statsmodels.tsa.vector_ar.var_model import VARProcess, VARResults
label_desc: Use image node_id 3 for calling the SVARProcess obj's underlying member method code with example usage: obj.svar_ma_rep(maxn, P) and returns: np