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)
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)
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)