def test_pareto_numeric():
xm, beta = Integer(3), Integer(2)
alpha = beta + 5
X = Pareto('x', xm, alpha)
assert E(X) == alpha*xm/(alpha - 1)
assert variance(X) == xm**2*alpha/(((alpha - 1)**2*(alpha - 2)))
def test_pareto():
xm, beta = symbols('xm beta', positive=True, finite=True)
alpha = beta + 5
X = Pareto('x', xm, alpha)
dens = density(X)
x = Symbol('x')
assert dens(x) == x**(-(alpha + 1))*alpha*xm**alpha
def test_prefab_sampling():
N = Normal('X', 0, 1)
L = LogNormal('L', 0, 1)
E = Exponential('Ex', 1)
P = Pareto('P', 1, 3)
W = Weibull('W', 1, 1)
U = Uniform('U', 0, 1)
B = Beta('B', 2, 5)
G = Gamma('G', 1, 3)
variables = [N, L, E, P, W, U, B, G]
niter = 10
for var in variables:
for i in range(niter):
assert sample(var) in var.pspace.domain.set