Chimpanzees

This is the third Chimpanzees model (m10.3) in Statistical Rethinking Edition 1.

Data

import CSV
import Random
import TuringModels

using DataFrames

Random.seed!(1)

file_path = joinpath(TuringModels.project_root, "data", "chimpanzees.csv")
df = CSV.read(file_path, DataFrame; delim=';');

Model

using StatsFuns
using Turing

@model function m10_3(y, x₁, x₂)
    α ~ Normal(0, 10)
    βp ~ Normal(0, 10)
    βpC ~ Normal(0, 10)

    logits = α .+ (βp .+ βpC * x₁) .* x₂
    y .~ BinomialLogit.(1, logits)
end

m10_3 (generic function with 2 methods)

Output

model = m10_3(df.pulled_left, df.condition, df.prosoc_left)
chns = sample(model, NUTS(), 2000)

Chains MCMC chain (2000×15×1 Array{Float64, 3}):

Iterations        = 1001:1:3000
Number of chains  = 1
Samples per chain = 2000
Wall duration     = 8.85 seconds
Compute duration  = 8.85 seconds
parameters        = α, βp, βpC
internals         = lp, n_steps, is_accept, acceptance_rate, log_density, hamiltonian_energy, hamiltonian_energy_error, max_hamiltonian_energy_error, tree_depth, numerical_error, step_size, nom_step_size

Summary Statistics
  parameters      mean       std   naive_se      mcse         ess      rhat   ess_per_sec
      Symbol   Float64   Float64    Float64   Float64     Float64   Float64       Float64

           α    0.0443    0.1225     0.0027    0.0036   1292.8804    1.0025      146.0717
          βp    0.6157    0.2170     0.0049    0.0066   1024.1444    1.0068      115.7095
         βpC   -0.0970    0.2625     0.0059    0.0073   1123.0485    1.0025      126.8838

Quantiles
  parameters      2.5%     25.0%     50.0%     75.0%     97.5%
      Symbol   Float64   Float64   Float64   Float64   Float64

           α   -0.2058   -0.0384    0.0432    0.1289    0.2768
          βp    0.1981    0.4748    0.6065    0.7651    1.0451
         βpC   -0.5995   -0.2755   -0.1015    0.0834    0.4159

using StatsPlots

StatsPlots.plot(chns)

"/home/runner/work/TuringModels.jl/TuringModels.jl/__site/assets/models/chimpanzees/code/output/chns.svg"

Original output

"""
      Mean StdDev lower 0.89 upper 0.89 n_eff Rhat
 a    0.05   0.13      -0.15       0.25  3284    1
 bp   0.62   0.22       0.28       0.98  3032    1
 bpC -0.11   0.26      -0.53       0.29  3184    1
""";