dist = np.zeros((size, size))
p_ij = np.zeros((size, size))
for i in range(size):
for j in range(size):
dist[i, j] = np.absolute(x[i] - x[j])
p_ij[i, j] = 1 / (1 + dist[i, j]**beta)
# CHANGE THIIIIIIIIIIIIS FROM GGP TO DOUBLEPL
# alpha_doublepl = alpha*(c**(tau-sigma))/tau
# t = (sigma*size/alpha_doublepl)**(1/sigma) # size è quella finale o originale?
# u = TruncPois.tpoissrnd(t*w0)
t = (sigma * size / alpha)**(1 / sigma)
u = TruncPois.tpoissrnd(t * w)
n = Updates.update_n(w, G, p_ij) # sui vecchi o nuovi w?
# output = MCMC("w_gibbs", "exptiltBFRY", iter, sigma=sigma_true, tau=tau_true, alpha=alpha_true, u=u_true,
# p_ij=p_ij, n=n_true)
output = MCMC("w_gibbs",
"GGP",
iter,
sigma_tau=0.08,
tau=tau,
sigma=sigma,
alpha=alpha,
u=u,
n=n,
p_ij=p_ij,
c=c,
w_init=w)
