def setup_class(cls):
# VAR with 2 variables and 3 lags
ar = [[[.1, .2], [.3, .4]], [[.5, .6], [.7, .8]], [[.9, 0], [-.1,
-.2]]]
arparams = np.array(ar)
ma = [[0, .1], [.2, -.3]]
maparams = np.array(ma)
# Note: The __init__ call should reshape this from (2, 2) to (1, 2, 2)
cls.varma = wold.VARParams(arparams, maparams)
intercept = np.array([1.2, 3.4])
cls.varma2 = wold.VARParams(arparams, maparams, intercept)
def test_neqs_mismatch(self):
# The number of equations implied by ar shape doesn't match that of ma
# 3-lag 2-equation 4MA VARMA
ar3 = np.random.randn(3, 2, 2)
ma4 = np.random.randn(4, 2, 2)
wold.VARParams(ar3, ma4)
with pytest.raises(ValueError):
# pass ma that suggests too few equations
wold.VARParams(ar3, ma4[:, :-1, :-1])
with pytest.raises(ValueError):
# pass ma with internally-inconsistent shape
wold.VARParams(ar3, ma4[:, :-1, :])
def test_invalid_shapes_var(self):
# 3-lag 2-equation VAR
ar3 = np.random.randn(3, 2, 2)
with pytest.raises(ValueError):
# too few dimensions
wold.VARParams(ar3[:, :, 0])
with pytest.raises(ValueError):
# shape[1] != shape[2]
wold.VARParams(ar3[:, :, :-1])
with pytest.raises(ValueError):
# len(shape) < 3
wold.VARParams(ar3[:, :, 0])
def test_invalid_intercept_var(self):
# 3-lag 2-equation VAR
ar3 = np.random.randn(3, 2, 2)
intercept = np.array([1, 2])
# smoke tests for valid paramaters
wold.VARParams(ar3)
wold.VARParams(ar3, intercept=intercept)
with pytest.raises(ValueError):
wold.VARParams(ar3, intercept=intercept.reshape(2, 1))
with pytest.raises(ValueError):
wold.VARParams(ar3, intercept=intercept.reshape(1, 2))
with pytest.raises(ValueError):
wold.VARParams(ar3, intercept=np.array(4))
def setup_class(cls):
ar = [[[1., 2, 3], [0, 1., 4], [0, 0, 1.]]]
# Choose AR params to be not-stationary
arparams = np.array(ar)
ma = [[[0, .1, -1], [.2, -.3, 0], [0.1, 2.1, -0.4]]]
maparams = np.array(ma)
cls.varma = wold.VARParams(arparams, maparams)
def setup_class(cls):
# AR Process that we'll treat as a VAR
ar = [1, -.25]
# Note that this induces an
# AR Polynomial L^0 - L^1 + .25 L^2 --> (1-.5L)**2
arparams = np.array(ar)
ma = []
maparams = np.array(ma)
cls.varma = wold.VARParams(arparams, maparams)
def test_equiv_construction(self):
# Test that passing np.array([]) or None as maparams is equivalent
varma = self.varma
other = wold.VARParams(varma.arcoefs, None)
assert (other.macoefs == varma.macoefs).all()