using Random
using Turing
using MCMCChains
using Distributions
using StatsPlots

#  真のサイコロ
p_true = 0.5
Ns = 100
Random.seed!(12)
data = rand(Bernoulli(p_true), Ns);

# Turingのモデル
@model coinflip(y) = begin
    # Our prior belief about the probability of heads in a coin.
    p ~ Beta(1, 1)
    
    # The number of observations.
    N = length(y)
    for n in 1:N
        # Heads or tails of a coin are drawn from a Bernoulli distribution.
        y[n] ~ Bernoulli(p)
    end
end;

# HMC
iterations = 1000
ϵ = 0.05
τ = 10
chain = sample(coinflip(data), HMC(ϵ, τ), iterations, progress=false);

# 描画
p_summary = chain[:p]
plot(p_summary, seriestype = :histogram)

plot(p_summary, seriestype = :histogram)

plot(p_summary, seriestype = :histogram, format=:png)