def get_aic(self, second_order=False):
"""returns Aikake Information Criteria
Parameters
----------
second_order
if true, the second
adjusted by the alignment length
"""
if second_order:
sequence_length = sum(
len(self.get_param_value("lht", locus=l).index)
for l in self.locus_names)
else:
sequence_length = None
lnL = self.get_log_likelihood()
nfp = self.get_num_free_params()
return aic(lnL, nfp, sequence_length)
def test_aic_corrected(self):
"""correctly compute AIC corrected for small sample size"""
# from Burnham & Anderson 2002, p102
assert_allclose(aic(-9.7039, 4, sample_size=13), 32.4078)
def test_aic(self):
"""correctly compute AIC from Burnham & Anderson 2002, p102"""
assert_allclose(aic(-9.7039, 4), 27.4078)
def test_aic(self):
"""correctly compute AIC from Burnham & Anderson 2002, p102"""
self.assertFloatEqual(aic(-9.7039, 4), 27.4078)