def test_figarch_recursion(self):
nobs, resids, = self.nobs, self.resids
sigma2, backcast = self.sigma2, self.backcast
parameters = np.array([1.0, 0.2, 0.4, 0.3])
fresids = resids**2
p = q = 1
trunc_lag = 1000
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs,
trunc_lag, backcast, self.var_bounds)
lam = rec.figarch_weights(parameters[1:], p, q, truncation=trunc_lag)
lam_rev = lam[::-1]
omega_tilde = parameters[0] / (1 - parameters[-1])
sigma2_direct = np.empty_like(sigma2)
for t in range(nobs):
backcasts = trunc_lag - t
sigma2_direct[t] = omega_tilde
if backcasts:
sigma2_direct[t] += backcast * lam_rev[:backcasts].sum()
if t:
sigma2_direct[t] += np.sum(lam_rev[-t:] *
fresids[max(0, t - 1000):t])
assert_almost_equal(sigma2_direct, sigma2)
recpy.figarch_recursion(parameters, fresids, sigma2, p, q, nobs,
trunc_lag, backcast, self.var_bounds)
sigma2_numba = sigma2.copy()
recpy.figarch_recursion_python(parameters, fresids, sigma2, p, q, nobs,
trunc_lag, backcast, self.var_bounds)
sigma2_python = sigma2.copy()
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs,
trunc_lag, backcast, self.var_bounds)
assert_almost_equal(sigma2_numba, sigma2)
assert_almost_equal(sigma2_python, sigma2)
def test_figarch_recursion(self):
nobs, resids, = self.nobs, self.resids
sigma2, backcast = self.sigma2, self.backcast
parameters = np.array([1.0, 0.2, 0.4, 0.3])
fresids = resids ** 2
p = q = 1
trunc_lag = 1000
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast,
self.var_bounds)
lam = rec.figarch_weights(parameters[1:], p, q, truncation=trunc_lag)
lam_rev = lam[::-1]
omega_tilde = parameters[0] / (1 - parameters[-1])
sigma2_direct = np.empty_like(sigma2)
for t in range(nobs):
backcasts = trunc_lag - t
sigma2_direct[t] = omega_tilde
if backcasts:
sigma2_direct[t] += backcast * lam_rev[:backcasts].sum()
if t:
sigma2_direct[t] += np.sum(lam_rev[-t:] * fresids[max(0, t - 1000):t])
assert_almost_equal(sigma2_direct, sigma2)
recpy.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast,
self.var_bounds)
sigma2_numba = sigma2.copy()
recpy.figarch_recursion_python(parameters, fresids, sigma2, p, q, nobs, trunc_lag,
backcast, self.var_bounds)
sigma2_python = sigma2.copy()
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast,
self.var_bounds)
assert_almost_equal(sigma2_numba, sigma2)
assert_almost_equal(sigma2_python, sigma2)
def test_figarch_performance(self):
midas_setup = """
p = q = 1
trunc_lag = 1000
parameters = np.array([1.0, 0.2, 0.2, 0.04])
fresids = resids ** 2.0
"""
midas_first = """
recpy.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast, var_bounds)
"""
midas_second = """
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast, var_bounds)
"""
timer = Timer(
midas_first,
"Numba",
midas_second,
"Cython",
"FIGARCH",
self.timer_setup + midas_setup,
)
timer.display()
assert timer.ratio < 10.0
if not (missing_numba or CYTHON_COVERAGE):
assert 0.1 < timer.ratio
def test_figarch_performance(self):
midas_setup = """
p = q = 1
trunc_lag = 1000
parameters = np.array([1.0, 0.2, 0.2, 0.04])
fresids = resids ** 2.0
"""
midas_first = """
recpy.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast, var_bounds)
"""
midas_second = """
rec.figarch_recursion(parameters, fresids, sigma2, p, q, nobs, trunc_lag, backcast, var_bounds)
"""
timer = Timer(midas_first, 'Numba', midas_second, 'Cython', 'FIGARCH',
self.timer_setup + midas_setup)
timer.display()
assert timer.ratio < 10.0
if not (missing_numba or CYTHON_COVERAGE):
assert 0.1 < timer.ratio
