def test_quantile_CI_monotone_alpha(args):
X, q, alpha = args
alpha1, alpha2 = sorted(alpha)
# Lot's of checks already inside quantile_CI
LB1, UB1 = qt.quantile_CI(X, q, alpha1) # This CI should be larger
LB2, UB2 = qt.quantile_CI(X, q, alpha2)
assert LB1 <= LB2
assert UB1 >= UB2
def test_quantile_CI_monotone_q(args):
X, q, alpha = args
q1, q2 = sorted(q)
# Lot's of checks already inside quantile_CI
LB1, UB1 = qt.quantile_CI(X, q1, alpha)
LB2, UB2 = qt.quantile_CI(X, q2, alpha)
assert LB1 <= LB2
assert UB1 <= UB2
def test_quantile_CI_monotone_x(args):
X, q, alpha = args
assume(len(X) >= 1)
LB1, UB1 = qt.quantile_CI(X, q, alpha)
X2 = np.copy(X)
X2[0] = -np.inf
LB2, UB2 = qt.quantile_CI(X2, q, alpha)
assert LB1 >= LB2
assert UB1 >= UB2
X2 = np.copy(X)
X2[0] = np.inf
LB2, UB2 = qt.quantile_CI(X2, q, alpha)
assert LB1 <= LB2
assert UB1 <= UB2
def test_quantile_and_CI(args):
X, q, alpha = args
estimate0, LB0, UB0 = qt.quantile_and_CI(X, q, alpha)
assert LB0 <= estimate0
assert estimate0 <= UB0
# Recompute without using _ internal funcs
LB, UB = qt.quantile_CI(X, q, alpha=alpha)
estimate = qt.quantile(X, q)
assert estimate0 == estimate
assert LB0 == LB
assert UB0 == UB
def mc_test_quantile_CI(mc_runs=1000,
n=2000,
q=0.5,
alpha=0.05,
random=np.random):
q0 = ss.norm.ppf(q)
X = random.randn(mc_runs, n)
R = np.array([qt.quantile_CI(xx, q) for xx in X])
LB, UB = R[:, 0], R[:, 1]
n_pass = np.sum((LB <= q0) & (q0 <= UB))
# This is only a one-sided test
pval = ss.binom.cdf(n_pass, mc_runs, 1 - alpha)
return pval
def test_min_quantile_CI(args):
X, q, m, alpha = args
estimate0, LB0, UB0 = qt.min_quantile_CI(X, q, m, alpha)
assert LB0 <= estimate0
assert estimate0 <= UB0
# Recompute without using _ internal funcs
q = 1.0 - (1.0 - q)**(1.0 / m)
LB, UB = qt.quantile_CI(X, q, alpha=alpha)
estimate = qt.quantile(X, q)
assert estimate0 == estimate
assert LB0 == LB
assert UB0 == UB
def test_quantile_CI(args):
X, q, alpha = args
idx_q = qt._quantile(len(X), q)
idx_l, idx_u = qt._quantile_CI(len(X), q, alpha)
assert idx_l <= idx_q
assert idx_q <= idx_u
# Lot's of checks already inside quantile_CI
LB, UB = qt.quantile_CI(X, q, alpha)
assert LB <= UB
estimate = qt.quantile(X, q)
assert LB <= estimate
assert estimate <= UB