def __init__(self, *args, **kwargs):
super(GumbelTest, self).__init__(*args, **kwargs)
self.datasets = [
portpirie().fields.sea_level,
fremantle().fields.sea_level
]
# The following values are obtained using ismev and extRemes R
# packages
self.expected_mle_params = [(0, 3.8694, 0.1949), (0, 1.4663, 0.1394)]
self.expected_mle_nnlf = [-4.2177, -39.1909]
self.expected_mle_se = [(0.02549, 0.01885), (0.01593, 0.01084)]
# The following values are obtained using lmom R package
self.expected_lmom_params = [(0, 3.8685, 0.1943), (0, 1.4690, 0.1195)]
def __init__(self, *args, **kwargs):
super(GumbelTest, self).__init__(*args, **kwargs)
self.datasets = [portpirie().fields.sea_level,
fremantle().fields.sea_level]
# The following values are obtained using ismev and extRemes R
# packages
self.expected_mle_params = [(0, 3.8694, 0.1949),
(0, 1.4663, 0.1394)]
self.expected_mle_nnlf = [-4.2177, -39.1909]
self.expected_mle_se = [(0.02549, 0.01885),
(0.01593, 0.01084)]
# The following values are obtained using lmom R package
self.expected_lmom_params = [(0, 3.8685, 0.1943),
(0, 1.4690, 0.1195)]
def __init__(self, *args, **kwargs):
super(GEVTest, self).__init__(*args, **kwargs)
self.datasets = [portpirie().fields.sea_level,
fremantle().fields.sea_level]
# The following values are obtained using ismev and extRemes R
# packages
self.expected_mle_params = [(-0.0501, 3.8747, 0.1980),
(-0.2174, 1.4823, 0.1413)]
self.expected_mle_nnlf = [-4.3391, -43.5667]
self.expected_mle_se = [(0.09826, 0.02793, 0.02025),
(0.06377, 0.01671, 0.01149)]
# The following values are obtained using extRemes R package
self.expected_lmom_params = [(-0.0515, 3.8732, 0.2031),
(-0.1963, 1.4807, 0.1391)]
def __init__(self, *args, **kwargs):
super(GEVTest, self).__init__(*args, **kwargs)
self.datasets = [
portpirie().fields.sea_level,
fremantle().fields.sea_level
]
# The following values are obtained using ismev and extRemes R
# packages
self.expected_mle_params = [(-0.0501, 3.8747, 0.1980),
(-0.2174, 1.4823, 0.1413)]
self.expected_mle_nnlf = [-4.3391, -43.5667]
self.expected_mle_se = [(0.09826, 0.02793, 0.02025),
(0.06377, 0.01671, 0.01149)]
# The following values are obtained using extRemes R package
self.expected_lmom_params = [(-0.0515, 3.8732, 0.2031),
(-0.1963, 1.4807, 0.1391)]
"""
Tests for classic module
"""
import pytest
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from skextremes.models.classic import GEV, Gumbel
from skextremes.datasets import portpirie, fremantle
# Datasets to be used
datasets = [portpirie().fields.sea_level, fremantle().fields.sea_level]
# Expected results for GEV
# The following values are obtained using ismev and extRemes R packages
expected_mle_params = [(-0.0501, 3.8747, 0.1980), (-0.2174, 1.4823, 0.1413)]
expected_mle_nnlf = [-4.3391, -43.5667]
expected_mle_se = [(0.09826, 0.02793, 0.02025), (0.06377, 0.01671, 0.01149)]
# The following values are obtained using extRemes R package
expected_lmom_params = [(-0.0515, 3.8732, 0.2031), (-0.1963, 1.4807, 0.1391)]
class TestGEV:
@pytest.mark.parametrize(
"data, params, nnlf, se",
[(d, p, n, s) for d, p, n, s in zip(
datasets,
expected_mle_params,
expected_mle_nnlf,
expected_mle_se,
)],
)
