def test_direct_simple(data):
mod = IV3SLS(data)
res = mod.fit(cov_type='unadjusted')
y = []
x = []
z = []
for key in data:
val = data[key]
if isinstance(val, tuple):
y.append(val[0])
nobs = val[0].shape[0]
v1 = val[1] if val[1] is not None else np.empty((nobs, 0))
v2 = val[2] if val[2] is not None else np.empty((nobs, 0))
v3 = val[3] if val[3] is not None else np.empty((nobs, 0))
x.append(np.concatenate([v1, v2], 1))
z.append(np.concatenate([v1, v3], 1))
if len(val) == 5:
return # weighted
else:
y.append(val['dependent'])
nobs = val['dependent'].shape[0]
vexog = val['exog'] if val['exog'] is not None else np.empty((nobs, 0))
vendog = val['endog'] if val['endog'] is not None else np.empty((nobs, 0))
vinstr = val['instruments'] if val['instruments'] is not None else np.empty((nobs, 0))
x.append(np.concatenate([vexog, vendog], 1))
z.append(np.concatenate([vexog, vinstr], 1))
if 'weights' in val:
return # weighted
out = simple_3sls(y, x, z)
assert_allclose(res.params.values, out.beta1.squeeze())
assert_allclose(res.sigma, out.sigma)
assert_allclose(res.resids.values, out.eps, atol=1e-4)
assert_allclose(np.diag(res.cov), np.diag(out.cov))
def test_single_equation(data):
key = list(data.keys())[0]
data = {key: data[key]}
mod = IV3SLS(data)
res = mod.fit(cov_type='unadjusted')
y = []
x = []
z = []
for key in data:
val = data[key]
if isinstance(val, tuple):
y.append(val[0])
x.append(np.concatenate([val[1], val[2]], 1))
z.append(np.concatenate([val[1], val[3]], 1))
if len(val) == 5:
return # weighted
else:
y.append(val['dependent'])
x.append(np.concatenate([val['exog'], val['endog']], 1))
z.append(np.concatenate([val['exog'], val['instruments']], 1))
if 'weights' in val:
return # weighted
out = simple_3sls(y, x, z)
assert_allclose(res.params.values, out.beta1.squeeze())
assert_allclose(res.sigma, out.sigma)
assert_allclose(res.resids.values, out.eps)
assert_allclose(np.diag(res.cov), np.diag(out.cov))
