def test_mle_fit(self):
for i in range(len(self.datasets)):
model = GEV(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 = 3)
assert_almost_equal(model._nnlf(params), self.expected_mle_nnlf[i],
decimal = 3)
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 = GEV(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=3)
assert_almost_equal(model._nnlf(params),
self.expected_mle_nnlf[i],
decimal=3)
assert_array_almost_equal(model._se,
self.expected_mle_se[i],
decimal=4)
def test_mle_fit(self, data, params, nnlf, se):
model = GEV(data, fit_method="mle", ci=0.05, ci_method="delta")
_params = (-model.c, model.loc, model.scale)
assert_array_almost_equal(_params, params, decimal=3)
assert_almost_equal(model._nnlf(params), nnlf, decimal=3)
assert_array_almost_equal(model._se, se, decimal=4)
