def prec_ci(self, alpha=0.05, hpd=True, hpd_draws=100000):
"""
Computes HPD or regular frequentist interval
"""
from statlib.tools import quantile
if hpd:
n, d = self.var_post_params
prec_post = stats.gamma(n / 2.0, scale=2.0 / d)
prec_draws = prec_post.rvs(hpd_draws)
qs = quantile(prec_draws, [alpha / 2, 0.5, 1 - alpha / 2])
hpd_lower, median, hpd_upper = qs
return hpd_lower, median, hpd_upper
else:
raise NotImplementedError
def prec_ci(self, alpha=0.05, hpd=True, hpd_draws=100000):
"""
Computes HPD or regular frequentist interval
"""
from statlib.tools import quantile
if hpd:
n, d = self.var_post_params
prec_post = stats.gamma(n / 2., scale=2. / d)
prec_draws = prec_post.rvs(hpd_draws)
qs = quantile(prec_draws, [alpha / 2, 0.5, 1 - alpha / 2])
hpd_lower, median, hpd_upper = qs
return hpd_lower, median, hpd_upper
else:
raise NotImplementedError
def boot_ci(sample, samples=10000):
draws = sample(samples)
return quantile(draws, [0.05, 0.95])