def test_params(data):
mod = IVSystemGMM(data.eqns, weight_type=data.weight_type)
res = mod.fit(cov_type=data.weight_type, iter_limit=data.steps)
simple = simple_gmm(data.y, data.x, data.z, data.robust, steps=data.steps)
if data.steps == 1:
beta = simple.beta0
else:
beta = simple.beta1
assert_allclose(res.params.values, beta, rtol=1e-4)
def test_cov(data):
mod = IVSystemGMM(data.eqns, weight_type=data.weight_type)
res = mod.fit(cov_type=data.weight_type, iter_limit=data.steps)
simple = simple_gmm(data.y, data.x, data.z, data.robust, steps=data.steps)
assert_allclose(np.asarray(res.cov), simple.cov)
def test_weights(data):
mod = IVSystemGMM(data.eqns, weight_type=data.weight_type)
res = mod.fit(cov_type=data.weight_type, iter_limit=data.steps)
simple = simple_gmm(data.y, data.x, data.z, data.robust, steps=data.steps)
w = simple.w0 if data.steps == 1 else simple.w1
assert_allclose(res.w, w, rtol=1e-4)
def test_j_statistic_direct(data):
mod = IVSystemGMM(data.eqns, weight_type=data.weight_type)
res = mod.fit(cov_type=data.weight_type, iter_limit=data.steps)
simple = simple_gmm(data.y, data.x, data.z, data.robust, steps=data.steps)
assert_allclose(res.j_stat.stat, simple.j_stat, rtol=1e-4)