def test_summary():
 np.random.seed(4323)
 n = 100
 exog = np.random.normal(size=(n, 2))
 exog[:, 0] = 1
 endog = np.random.normal(size=n)
 for method in ('irls', 'cg'):
  fa = sm.families.Gaussian()
  model = sm.GLM(endog, exog, family=fa)
  rslt = model.fit(method=method)
  s = rslt.summary()

def test_summary ( ) : np . random . seed ( 4323 ) n = 100 exog = np . random . normal ( size = ( n , 2 ) ) exog [ : , 0 ] = 1 endog = np . random . normal ( size = n ) for method in ( 'irls' , 'cg' ) : fa = sm . families . Gaussian ( ) model = sm . GLM ( endog , exog , family = fa ) rslt = model . fit ( method = method ) s = rslt . summary ( )
smoke test for summary .