def random(a, t, b):
u = ds.rg0()
v = gamma.random(a, t)
vv = gamma.random(a + 1, t)
if (u <= (t / (b + t))):
return v
return vv
def random(a, b, t, g, c):
u = ds.rg0()
v1 = gamma.random(a, t)
v2 = gamma.random(a + 1, t)
if (u <= t / (b + t)):
return g * math.pow(v1, 1 / c)
return g * math.pow(v2, 1 / c)
def random(t):
u = ds.rg0()
v = exponential.random(t)
w = gamma.random(3, t)
if (u <= t / (1 + t)):
return v
return w
def random(a,t):
u=uniform.random(0,1)
v=exponential.random(t)
w=gamma.random(3,t)
if(u<a/(1+a)):
return v
return w
def random(t):
return gamma.random(t,4)
def random(aa, bb, mu, lmbda):
n = gamma.random(aa, bb)
return normal.random(mu, math.sqrt(1 / (lmbda * n)))
def random(z, l, a, g):
return z + l * math.log(gamma.random(g, 1) / gamma.random(a, 1))
def random(b, aa, bb):
return max(exponential.random(b),
b - gamma.random(aa, bb) * math.log(-math.log(r.random())))
def random(a, s, aa, gmma, bb):
return a + s * math.pow(
(gamma.random(aa, 1) / gamma.random(gmma, 1)), 1 / bb)
def random(a,b):
return poisson.random(gamma.random(a,b))
def random(a, theta, aa, bb):
return a + theta * math.pow(gamma.random(aa, 1), 1 / bb)
def random(a, K):
yy = np.zeros(a.shape)
for i in range(K):
yy[i][0] = gamma.random(a[i][0], 1)
yy /= np.sum(yy)
return yy
def random(aa, bb):
if (aa <= 0 or bb <= 0):
raise ValueError("aa and bb must be greater than 0")
return gamma.random(aa, 1) / gamma.random(bb, 1)
def random(a,b):
return 1/gamma.random(a,b)
def random(a, b):
c = gamma.random(b, 1)
while (c == 0):
c = gamma.random(b, 1)
return gamma.random(a, 1) / c
def random(s,k):
return gamma.random(2*(s**2),k/2.0)
def random(a,b):
return math.exp(gamma.random(-1/b,a))
def random(a, b):
return math.sqrt(exponential.random(1) * gamma.random(a, b / a))
def random(aa, bb):
if (aa <= 0 or bb <= 0):
raise ValueError("aa and bb must be bigger than 0")
x = gamma.random(aa, 1)
return x / (x + gamma.random(bb, 1))
def random(s, m):
return normal.random(0, s) / math.sqrt(gamma.random(1 / 2, m - 1 / 2))
def random(mu, sigma, gmma, d1, d2):
return mu + sigma * math.pow(
gamma.random(d1, 1) / gamma.random(d2, 1), gmma)