def fast_etienne_likelihood(mod, params, kda=None, kda_x=None):
'''
same as Abundance inner function, but takes advantage of constant
m value when varying only theta.
:argument abd: Abundance object
:argument params: list containing theta and m
:argument kda_x: precomputed list of exp(kda + ind*immig)
'''
theta = params[0]
immig = float (params[1]) / (1 - params[1]) * (mod.community.J - 1)
log_immig = log (immig)
theta_s = theta + mod.community.S
if not kda_x:
kda_x = [exp(mod._kda[val] + val * log_immig) for val in \
xrange (mod.community.J - mod.community.S)]
poch1 = exp (mod._factor + log (theta) * mod.community.S - \
lpoch (immig, mod.community.J) + \
log_immig * mod.community.S + lngamma(theta))
gam_theta_s = gamma (theta_s)
lik = mpfr(0.0)
for val in xrange (mod.community.J - mod.community.S):
lik += poch1 * kda_x[val] / gam_theta_s
gam_theta_s *= theta_s + val
return ((-log (lik)), kda_x)
def likelihood(self, params):
'''
log-likelihood function
:argument params: a list of 2 parameters:
* theta = params[0]
* m = params[1]
:returns: log likelihood of given theta and I
'''
kda = self._kda
theta = params[0]
immig = float(params[1]) / (1 - params[1]) * (self.community.J - 1)
log_immig = log(immig)
theta_s = theta + self.community.S
poch1 = exp(self._factor + log(theta) * self.community.S - \
lpoch(immig, self.community.J) + \
log_immig * self.community.S + lngamma(theta))
gam_theta_s = gamma(theta_s)
lik = mpfr(0.0)
for abd in xrange(int(self.community.J - self.community.S)):
lik += poch1 * exp(kda[abd] + abd * log_immig) / gam_theta_s
gam_theta_s *= theta_s + abd
return -log(lik)
def lpoch (z, m):
'''
returns log Pochhammer symbol taking advantage of:
Pochhammer symbol (z)_m = (z)(z+1)....(z+m-1) = gamma(z+m)/gamma(z)
'''
return lngamma(z+m) - lngamma(z)
