def random(self, size=None):
mu = self.mu
lam = self.lam
alpha = self.alpha
v = rnormal(loc=0., scale=1., size=size)**2
x = mu + (mu**2) * v / (2. * lam) - mu / (
2. * lam) * sqrt(4. * mu * lam * v + (mu * v)**2)
z = runiform(low=0., high=1., size=size)
# i = z > mu / (mu + x)
# x[i] = (mu**2) / x[i]
i = floor(z - mu / (mu + x)) * 2 + 1
x = (x**-i) * (mu**(i + 1))
return x + alpha
def random(size=None):
return runiform(upper, lower, size)
def random(self, size=None):
return runiform(self.upper, self.lower, size)
def random(self, size=None):
return runiform(self.upper, self.lower, size)
def random(size=None):
return runiform(upper, lower, size)
from numpy import zeros
xdim = 100
cmatrix = zeros((xdim,xdim))
cblank = zeros((xdim,xdim))
chybrid = zeros((xdim,xdim))
i = 0
while i < xdim:
j = i + 1
cmatrix[i,i] = 1
cblank[i,i] = 1
chybrid[i,i] = 1
while j < xdim:
rho = runiform(0.9,1,1)
cmatrix[i,j] = rho
cmatrix[j,i] = rho
if i < xdim/2:
if j < xdim/2:
chybrid[i,j]=rho
chybrid[j,i]=rho
j = j + 1
i = i + 1
nummodels = 5
beta0 = zeros(nummodels)
beta = zeros((xdim,nummodels))
def random(self, size=None):
u = runiform(low=0., high=1., size=size)
n = rnormal(self.mu, self.sigma, size=size)
return n - self.nu * log(u)