def test_hess_fun1_fd(self):
for test_params in self.params:
#hetrue = 0
hetrue = self.hesstrue(test_params)
if hetrue is not None: #Hessian does not work for 2d return of fun
fun = self.fun()
#default works, epsilon 1e-6 or 1e-8 is not precise enough
hefd = numdiff.approx_hess1(
test_params,
fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
#TODO: I reduced precision to DEC3 from DEC4 because of
# TestDerivativeFun
hefd = numdiff.approx_hess2(
test_params,
fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
hefd = numdiff.approx_hess3(
test_params,
fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
def hessian(self, params):
'''Hessian of loglikelihood calculated by numerical differentiation
Note: import requires statsmodels master
'''
from statsmodels.tools.numdiff import approx_hess1
# need options for hess (epsilon)
return approx_hess1(params, self.loglike)
def hessian(self, params):
'''Hessian of loglikelihood calculated by numerical differentiation
Note: import requires statsmodels master
'''
from statsmodels.tools.numdiff import approx_hess1
# need options for hess (epsilon)
return approx_hess1(params, self.loglike)
def test_hess(self):
for test_params in self.params:
he = self.mod.hessian(test_params)
hefd = numdiff.approx_fprime_cs(test_params, self.mod.score)
assert_almost_equal(he, hefd, decimal=DEC8)
#NOTE: notice the accuracy below
assert_almost_equal(he, hefd, decimal=7)
hefd = numdiff.approx_fprime(test_params,
self.mod.score,
centered=True)
assert_allclose(he, hefd, rtol=1e-9)
hefd = numdiff.approx_fprime(test_params,
self.mod.score,
centered=False)
assert_almost_equal(he, hefd, decimal=4)
hescs = numdiff.approx_fprime_cs(test_params.ravel(),
self.mod.score)
assert_allclose(he, hescs, rtol=1e-13)
hecs = numdiff.approx_hess_cs(test_params.ravel(),
self.mod.loglike)
assert_allclose(he, hecs, rtol=1e-9)
#NOTE: Look at the lack of precision - default epsilon not always
#best
grad = self.mod.score(test_params)
hecs, gradcs = numdiff.approx_hess1(test_params,
self.mod.loglike,
1e-6,
return_grad=True)
assert_almost_equal(he, hecs, decimal=1)
assert_almost_equal(grad, gradcs, decimal=1)
hecs, gradcs = numdiff.approx_hess2(test_params,
self.mod.loglike,
1e-4,
return_grad=True)
assert_almost_equal(he, hecs, decimal=3)
assert_almost_equal(grad, gradcs, decimal=1)
hecs = numdiff.approx_hess3(test_params, self.mod.loglike, 1e-5)
assert_almost_equal(he, hecs, decimal=4)
def test_hess_fun1_fd(self):
for test_params in self.params:
#hetrue = 0
hetrue = self.hesstrue(test_params)
if not hetrue is None: #Hessian doesn't work for 2d return of fun
fun = self.fun()
#default works, epsilon 1e-6 or 1e-8 is not precise enough
hefd = numdiff.approx_hess1(test_params, fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
#TODO: I reduced precision to DEC3 from DEC4 because of
# TestDerivativeFun
hefd = numdiff.approx_hess2(test_params, fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
hefd = numdiff.approx_hess3(test_params, fun, #epsilon=1e-8,
# TODO: should be kwds
args=self.args)
assert_almost_equal(hetrue, hefd, decimal=DEC3)
def test_hess(self):
for test_params in self.params:
he = self.mod.hessian(test_params)
hefd = numdiff.approx_fprime_cs(test_params, self.mod.score)
assert_almost_equal(he, hefd, decimal=DEC8)
#NOTE: notice the accuracy below
assert_almost_equal(he, hefd, decimal=7)
hefd = numdiff.approx_fprime(test_params, self.mod.score,
centered=True)
assert_allclose(he, hefd, rtol=1e-9)
hefd = numdiff.approx_fprime(test_params, self.mod.score,
centered=False)
assert_almost_equal(he, hefd, decimal=4)
hescs = numdiff.approx_fprime_cs(test_params.ravel(),
self.mod.score)
assert_allclose(he, hescs, rtol=1e-13)
hecs = numdiff.approx_hess_cs(test_params.ravel(),
self.mod.loglike)
assert_allclose(he, hecs, rtol=1e-9)
#NOTE: Look at the lack of precision - default epsilon not always
#best
grad = self.mod.score(test_params)
hecs, gradcs = numdiff.approx_hess1(test_params, self.mod.loglike,
1e-6, return_grad=True)
assert_almost_equal(he, hecs, decimal=1)
assert_almost_equal(grad, gradcs, decimal=1)
hecs, gradcs = numdiff.approx_hess2(test_params, self.mod.loglike,
1e-4, return_grad=True)
assert_almost_equal(he, hecs, decimal=3)
assert_almost_equal(grad, gradcs, decimal=1)
hecs = numdiff.approx_hess3(test_params, self.mod.loglike, 1e-5)
assert_almost_equal(he, hecs, decimal=4)
def _approx_hess1_backward(x, f, epsilon=None, args=(), kwargs=None):
n = len(x)
epsilon = -np.abs(_get_epsilon(x, 3, epsilon, n))
return approx_hess1(x, f, epsilon, args, kwargs, centered=False)
def _approx_hess1_backward(x, f, epsilon=None, args=(), kwargs=None):
n = len(x)
kwargs = {} if kwargs is None else kwargs
epsilon = -np.abs(_get_epsilon(x, 3, epsilon, n))
return approx_hess1(x, f, epsilon, args, kwargs)
