MCMC

from scipy.stats import gamma, poisson
import numpy as np
from empiricaldist import Pmf

alpha = 1.4
dist = gamma(alpha)

lams = np.linspace(0, 10, 101)
prior_pmf = Pmf(dist.pdf(lams), lams)
prior_pmf.normalize()

data = 4
likelihood = poisson.pmf(data, lams)
posterior = prior_pmf * likelihood
posterior.normalize()

np.float64(0.05015532557804499)

사전예측분포

sample_prior = dist.rvs(1000)
sample_prior_pred = poisson.rvs(sample_prior)
pmf_prior_pred = Pmf.from_seq(sample_prior_pred)

MCMC