def multigammaln(a, p):
"""Multivariate Log Gamma
Parameters
----------
a: tensor like
p: int
degrees of freedom. p > 0
"""
i = at.arange(1, p + 1)
return p * (p - 1) * at.log(np.pi) / 4.0 + at.sum(gammaln(a + (1.0 - i) / 2.0), axis=0)
def betaln(x, y):
return gammaln(x) + gammaln(y) - gammaln(x + y)
def factln(n):
return gammaln(n + 1)