def test_empty_coeff(self):
process = wold.ARMAParams()
assert_equal(process.arcoefs, np.array([]))
assert_equal(process.macoefs, np.array([]))
process = wold.ARMAParams([1, -0.8])
assert_equal(process.arcoefs, np.array([0.8]))
assert_equal(process.macoefs, np.array([]))
process = wold.ARMAParams(ma=[1, -0.8])
assert_equal(process.arcoefs, np.array([]))
assert_equal(process.macoefs, np.array([-0.8]))
def test_invalid_poly(self):
# check that passing invalid parameters to ARMAParams raise as expected
good = np.array([1.0, -0.5])
bad = np.array([-0.5])
# smoke check that valid params _dont_ raise
wold.ARMAParams(good, good)
for other in [good, bad, None]:
with pytest.raises(ValueError):
wold.ARMAParams(other, bad)
with pytest.raises(ValueError):
wold.ARMAParams(bad, other)
def test_invalid_shapes_arma(self):
# check that passing params with invalid shapes to ARMAParams/VARParams
# raises as expected
# 1-dimensional case
good = np.array([1, .34, -.2])
# Check that correct params dont raise
wold.ARMAParams(good, None)
wold.ARMAParams(None, good)
for bad in [np.array(1), good.reshape(1, 3), good.reshape(3, 1, 1)]:
with pytest.raises(ValueError):
wold.ARMAParams(good, bad)
with pytest.raises(ValueError):
wold.ARMAParams(bad, good)
def test_from_coeff(self):
ar = [1.8, -0.9]
ma = [0.3]
process = wold.ARMAParams.from_coeffs(np.array(ar), np.array(ma))
ar.insert(0, -1)
ma.insert(0, 1)
ar_p = -1 * np.array(ar)
ma_p = ma
process_direct = wold.ARMAParams(ar_p, ma_p)
assert_equal(process.arcoefs, process_direct.arcoefs)
assert_equal(process.macoefs, process_direct.macoefs)
# assert_equal(process.nobs, process_direct.nobs)
# nobs from upstream deprecated
assert_equal(process.maroots, process_direct.maroots)
assert_equal(process.arroots, process_direct.arroots)
assert_equal(process.isinvertible, process_direct.isinvertible)
assert_equal(process.isstationary, process_direct.isstationary)
def test_from_model(self):
from sm2.tsa.arima_model import ARMA
process = wold.ARMAParams([1, -.8], [1, .3], 1000)
t = 1000
rs = np.random.RandomState(12345)
y = process.generate_sample(t, burnin=100, distrvs=rs.standard_normal)
res = ARMA(y, (2, 2)).fit(disp=False)
# upstream uses (1, 1), but we use (2, 2) to smoke-test
# a few lines in ARMATransparams
process_model = wold.ARMAParams.from_estimation(res)
process_coef = wold.ARMAParams.from_coeffs(res.arparams, res.maparams)
# Note: upstream also passes `t` to from_coeffs above
assert_equal(process_model.arcoefs, process_coef.arcoefs)
assert_equal(process_model.macoefs, process_coef.macoefs)
# assert_equal(process_model.nobs, process_coef.nobs)
# nobs from upstream deprecated
assert_equal(process_model.isinvertible, process_coef.isinvertible)
assert_equal(process_model.isstationary, process_coef.isstationary)
def setup_class(cls):
# Basic AR(1)
cls.ar = [1, -0.5]
cls.ma = [1]
cls.arma = wold.ARMAParams(cls.ar, cls.ma)
def test_periodogram(self):
process = wold.ARMAParams()
pg = process.periodogram()
assert_almost_equal(pg[0], np.linspace(0, np.pi, 100, False))
assert_almost_equal(pg[1], np.sqrt(2 / np.pi) / 2 * np.ones(100))