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)