def f(sp_sub, a1, a2):
return pm.stukel_invlogit(sp_sub,a1,a2)
def survey_likelihood(sp_sub, survey_plan, data, i, a1, a2):
data_ = np.ones_like(sp_sub)*data[i]
return pm.binomial_like(data_, survey_plan.n[i], pm.stukel_invlogit(sp_sub, a1, a2))
def simdata_postproc(sp_sub, survey_plan, a1, a2):
p = pm.stukel_invlogit(sp_sub, a1, a2)
n = survey_plan.n
return pm.rbinomial(n, p)
def f(sp_sub, a, x):
p = pm.stukel_invlogit(sp_sub(x), *a)
return p
def f(sp_sub, a, n=n):
return pm.rbinomial(n=n, p=pm.stukel_invlogit(sp_sub, *a))
def f(sp_sub, a, x):
p = pm.stukel_invlogit(sp_sub(x), *a)
return 2 * p * (1 - p) + p ** 2
