def test_ic():
#test information criteria
#consistency check
ics = [aic, aicc, bic, hqic]
ics_sig = [aic_sigma, aicc_sigma, bic_sigma, hqic_sigma]
for ic, ic_sig in zip(ics, ics_sig):
assert_(ic(np.array(2),10,2).dtype == np.float, msg=repr(ic))
assert_(ic_sig(np.array(2),10,2).dtype == np.float, msg=repr(ic_sig) )
assert_almost_equal(ic(-10./2.*np.log(2.),10,2)/10,
ic_sig(2, 10, 2),
decimal=14)
assert_almost_equal(ic_sig(np.log(2.),10,2, islog=True),
ic_sig(2, 10, 2),
decimal=14)
#examples penalty directly from formula
n, k = 10, 2
assert_almost_equal(aic(0, 10, 2), 2*k, decimal=14)
#next see Wikipedia
assert_almost_equal(aicc(0, 10, 2),
aic(0, n, k) + 2*k*(k+1.)/(n-k-1.), decimal=14)
assert_almost_equal(bic(0, 10, 2), np.log(n)*k, decimal=14)
assert_almost_equal(hqic(0, 10, 2), 2*np.log(np.log(n))*k, decimal=14)
def hqic(self):
"""
(float) Hannan-Quinn Information Criterion
"""
# return (-2 * self.llf +
# 2 * np.log(np.log(self.nobs_effective)) * self.df_model)
return hqic(self.llf, self.nobs_effective, self.df_model)
def test_ic():
#test information criteria
#consistency check
ics = [aic, aicc, bic, hqic]
ics_sig = [aic_sigma, aicc_sigma, bic_sigma, hqic_sigma]
for ic, ic_sig in zip(ics, ics_sig):
assert_(ic(np.array(2), 10, 2).dtype == np.float, msg=repr(ic))
assert_(ic_sig(np.array(2), 10, 2).dtype == np.float, msg=repr(ic_sig))
assert_almost_equal(ic(-10. / 2. * np.log(2.), 10, 2) / 10,
ic_sig(2, 10, 2),
decimal=14)
assert_almost_equal(ic_sig(np.log(2.), 10, 2, islog=True),
ic_sig(2, 10, 2),
decimal=14)
#examples penalty directly from formula
n, k = 10, 2
assert_almost_equal(aic(0, 10, 2), 2 * k, decimal=14)
#next see Wikipedia
assert_almost_equal(aicc(0, 10, 2),
aic(0, n, k) + 2 * k * (k + 1.) / (n - k - 1.),
decimal=14)
assert_almost_equal(bic(0, 10, 2), np.log(n) * k, decimal=14)
assert_almost_equal(hqic(0, 10, 2), 2 * np.log(np.log(n)) * k, decimal=14)
def test_ic():
# test information criteria
# examples penalty directly from formula
n = 10
k = 2
assert_almost_equal(aic(0, 10, 2), 2*k, decimal=14)
# next see Wikipedia
assert_almost_equal(aicc(0, 10, 2),
aic(0, n, k) + 2*k*(k+1.)/(n-k-1.), decimal=14)
assert_almost_equal(bic(0, 10, 2), np.log(n)*k, decimal=14)
assert_almost_equal(hqic(0, 10, 2), 2*np.log(np.log(n))*k, decimal=14)
def test_ic():
# test information criteria
# examples penalty directly from formula
n = 10
k = 2
assert_almost_equal(aic(0, 10, 2), 2*k, decimal=14)
# next see Wikipedia
assert_almost_equal(aicc(0, 10, 2),
aic(0, n, k) + 2*k*(k+1.)/(n-k-1.), decimal=14)
assert_almost_equal(bic(0, 10, 2), np.log(n)*k, decimal=14)
assert_almost_equal(hqic(0, 10, 2), 2*np.log(np.log(n))*k, decimal=14)
def hqic(self):
"""
(float) Hannan-Quinn Information Criterion
"""
# return -2*self.llf + 2*np.log(np.log(self.nobs))*self.params.shape[0]
return hqic(self.llf, self.nobs, self.params.shape[0])
def hqic(self):
"""
(float) Hannan-Quinn Information Criterion
"""
# return -2*self.llf + 2*np.log(np.log(self.nobs))*self.params.shape[0]
return hqic(self.llf, self.nobs, self.params.shape[0])