def test_plot_summary(self, data):
     model = Gumbel(data, fit_method="mle", ci=0.05, ci_method="delta")
     fig, ax1, ax2, ax3, ax4 = model.plot_summary()
     assert len(fig.get_axes()) == 4
     assert ax1.has_data()
     assert ax2.has_data()
     assert ax3.has_data()
     assert ax4.has_data()
 def test_plot_summary(self):
     for i in range(len(self.datasets)):
         model = Gumbel(self.datasets[i], 
                        fit_method = "mle", 
                        ci = 0.05, 
                        ci_method='delta')
         fig, ax1, ax2, ax3, ax4 = model.plot_summary()
         self.assertEqual(len(fig.get_axes()), 4)
         self.assertTrue(ax1.has_data())
         self.assertTrue(ax2.has_data())
         self.assertTrue(ax3.has_data())
         self.assertTrue(ax4.has_data())
Example #3
0
 def test_plot_summary(self):
     for i in range(len(self.datasets)):
         model = Gumbel(self.datasets[i],
                        fit_method="mle",
                        ci=0.05,
                        ci_method='delta')
         fig, ax1, ax2, ax3, ax4 = model.plot_summary()
         self.assertEqual(len(fig.get_axes()), 4)
         self.assertTrue(ax1.has_data())
         self.assertTrue(ax2.has_data())
         self.assertTrue(ax3.has_data())
         self.assertTrue(ax4.has_data())
 def test_mle_fit(self):
     for i in range(len(self.datasets)):
         model = Gumbel(self.datasets[i], 
                       fit_method = "mle", 
                       ci = 0.05, 
                       ci_method='delta')
         params = (-model.c, model.loc, model.scale)
         assert_array_almost_equal(params, self.expected_mle_params[i], 
                                   decimal = 4)
         assert_almost_equal(model._nnlf(params), self.expected_mle_nnlf[i],
                             decimal = 4)
         assert_array_almost_equal(model._se, self.expected_mle_se[i],
                             decimal = 4)
Example #5
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 def test_mle_fit(self):
     for i in range(len(self.datasets)):
         model = Gumbel(self.datasets[i],
                        fit_method="mle",
                        ci=0.05,
                        ci_method='delta')
         params = (-model.c, model.loc, model.scale)
         assert_array_almost_equal(params,
                                   self.expected_mle_params[i],
                                   decimal=4)
         assert_almost_equal(model._nnlf(params),
                             self.expected_mle_nnlf[i],
                             decimal=4)
         assert_array_almost_equal(model._se,
                                   self.expected_mle_se[i],
                                   decimal=4)
Example #6
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 def test_lmoments_fit(self):
     for i in range(len(self.datasets)):
         model = Gumbel(self.datasets[i], fit_method="lmoments")
         params = (-model.c, model.loc, model.scale)
         assert_array_almost_equal(params,
                                   self.expected_lmom_params[i],
                                   decimal=3)
 def test_lmoments_fit(self, data, params):
     model = Gumbel(data, fit_method="lmoments")
     _params = (-model.c, model.loc, model.scale)
     assert_array_almost_equal(_params, params, decimal=3)
 def test_mle_fit(self, data, params, nnlf, se):
     model = Gumbel(data, fit_method="mle", ci=0.05, ci_method="delta")
     _params = (-model.c, model.loc, model.scale)
     assert_array_almost_equal(_params, params, decimal=4)
     assert_almost_equal(model._nnlf(params), nnlf, decimal=4)
     assert_array_almost_equal(model._se, se, decimal=4)