This model is not executed on each change because it is similar to multivariate-chimpanzees-priors.
import Random
using TuringModels
using LinearAlgebra
Random.seed!(1)
# This script requires latest LKJ bijectors support.
# `] add Bijectors#master` to get latest Bijectors.
data_path = joinpath(@__DIR__, "..", "..", "data", "chimpanzees.csv")
delim = ";"
d = CSV.read(data_path, DataFrame; delim)
d.block_id = d.block
# m13.6nc1 is equivalent to m13.6nc in following Turing model
@model m13_6_nc(actor, block_id, condition, prosoc_left, pulled_left) = begin
# fixed priors
Rho_block ~ LKJ(3, 4.)
Rho_actor ~ LKJ(3, 4.)
sigma_block ~ filldist(truncated(Cauchy(0, 2), 0, Inf), 3)
sigma_actor ~ filldist(truncated(Cauchy(0, 2), 0, Inf), 3)
a ~ Normal(0, 1)
bp ~ Normal(0, 1)
bpc ~ Normal(0, 1)
# adaptive NON-CENTERED priors
Rho_block = (Rho_block' + Rho_block) / 2
Rho_actor = (Rho_actor' + Rho_actor) / 2
L_Rho_block = cholesky(Rho_block).L
L_Rho_actor = cholesky(Rho_actor).L
z_N_block ~ filldist(Normal(0, 1), 3, 6)
z_N_actor ~ filldist(Normal(0, 1), 3, 7)
# @show size(L_Rho_block) size(sigma_block) size(z_N_block_id)
a_block_bp_block_bpc_block = sigma_block .* L_Rho_block * z_N_block
a_actor_bp_actor_bpc_actor = sigma_actor .* L_Rho_actor * z_N_actor
a_block = a_block_bp_block_bpc_block[1, :]
bp_block = a_block_bp_block_bpc_block[2, :]
bpc_block = a_block_bp_block_bpc_block[3, :]
a_actor = a_actor_bp_actor_bpc_actor[1, :]
bp_actor = a_actor_bp_actor_bpc_actor[2, :]
bpc_actor = a_actor_bp_actor_bpc_actor[3, :]
# linear models
BPC = bpc .+ bpc_actor[actor] + bpc_block[block_id]
BP = bp .+ bp_actor[actor] + bp_block[block_id]
A = a .+ a_actor[actor] + a_block[block_id]
logit_p = A + (BP + BPC .* condition) .* prosoc_left
# likelihood
pulled_left .~ BinomialLogit.(1, logit_p)
end
chns = sample(
m13_6_nc(d.actor, d.block_id, d.condition, d.prosoc_left, d.pulled_left),
Turing.NUTS(0.95),
1000
)
chns |> display
m_13_6_nc_rethinking = """
Inference for Stan model: 78757717ec3ffa528c3819708907eb7f.
3 chains, each with iter=5000; warmup=1000; thin=1;
post-warmup draws per chain=4000, total post-warmup draws=12000.
mean se_mean sd 2.5% 25% 50% 75% 97.5%
z_N_block_id[1,1] -0.44 0.01 0.90 -2.17 -1.03 -0.46 0.13 1.39
z_N_block_id[1,2] 0.21 0.01 0.86 -1.50 -0.35 0.22 0.78 1.89
z_N_block_id[1,3] 0.34 0.01 0.87 -1.42 -0.22 0.35 0.92 2.02
z_N_block_id[1,4] -0.02 0.01 0.84 -1.71 -0.56 -0.03 0.52 1.63
z_N_block_id[1,5] -0.09 0.01 0.84 -1.73 -0.64 -0.10 0.47 1.56
z_N_block_id[1,6] 0.01 0.01 0.92 -1.85 -0.59 0.03 0.63 1.80
z_N_block_id[2,1] -0.37 0.01 0.82 -1.99 -0.90 -0.37 0.15 1.27
z_N_block_id[2,2] -0.18 0.01 0.78 -1.76 -0.66 -0.17 0.31 1.38
z_N_block_id[2,3] -0.36 0.01 0.79 -1.93 -0.87 -0.35 0.16 1.18
z_N_block_id[2,4] 0.23 0.01 0.77 -1.33 -0.26 0.23 0.72 1.74
z_N_block_id[2,5] 0.04 0.01 0.76 -1.49 -0.46 0.04 0.52 1.58
z_N_block_id[2,6] 1.01 0.01 0.84 -0.76 0.49 1.04 1.56 2.58
z_N_block_id[3,1] -0.59 0.01 0.91 -2.32 -1.20 -0.61 0.00 1.28
z_N_block_id[3,2] 0.28 0.01 0.88 -1.50 -0.29 0.28 0.86 2.04
z_N_block_id[3,3] 0.32 0.01 0.89 -1.46 -0.26 0.34 0.91 2.09
z_N_block_id[3,4] -0.11 0.01 0.89 -1.87 -0.69 -0.10 0.46 1.64
z_N_block_id[3,5] -0.12 0.01 0.86 -1.83 -0.68 -0.12 0.43 1.64
z_N_block_id[3,6] 0.20 0.01 0.91 -1.63 -0.40 0.20 0.81 1.99
L_Rho_block[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00
L_Rho_block[1,2] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_block[1,3] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_block[2,1] -0.06 0.00 0.32 -0.65 -0.29 -0.06 0.17 0.57
L_Rho_block[2,2] 0.94 0.00 0.07 0.73 0.92 0.97 0.99 1.00
L_Rho_block[2,3] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_block[3,1] 0.04 0.00 0.32 -0.57 -0.19 0.04 0.27 0.63
L_Rho_block[3,2] -0.04 0.00 0.31 -0.62 -0.26 -0.04 0.18 0.57
L_Rho_block[3,3] 0.89 0.00 0.10 0.64 0.84 0.92 0.97 1.00
z_N_actor[1,1] -0.49 0.01 0.36 -1.25 -0.71 -0.46 -0.24 0.15
z_N_actor[1,2] 1.99 0.01 0.62 0.88 1.55 1.96 2.40 3.29
z_N_actor[1,3] -0.63 0.01 0.38 -1.44 -0.87 -0.60 -0.35 0.04
z_N_actor[1,4] -0.65 0.01 0.39 -1.48 -0.89 -0.61 -0.37 0.03
z_N_actor[1,5] -0.48 0.01 0.36 -1.25 -0.71 -0.45 -0.23 0.15
z_N_actor[1,6] 0.09 0.00 0.33 -0.56 -0.13 0.09 0.30 0.75
z_N_actor[1,7] 0.73 0.01 0.41 0.04 0.45 0.69 0.98 1.62
z_N_actor[2,1] 0.06 0.01 0.83 -1.60 -0.49 0.07 0.59 1.71
z_N_actor[2,2] 0.14 0.01 0.99 -1.80 -0.52 0.14 0.81 2.07
z_N_actor[2,3] 0.38 0.01 0.86 -1.34 -0.18 0.38 0.95 2.04
z_N_actor[2,4] 0.25 0.01 0.85 -1.46 -0.29 0.26 0.81 1.91
z_N_actor[2,5] 0.13 0.01 0.84 -1.57 -0.41 0.13 0.68 1.79
z_N_actor[2,6] -0.62 0.01 0.87 -2.26 -1.20 -0.65 -0.09 1.20
z_N_actor[2,7] -0.04 0.01 0.92 -1.84 -0.66 -0.04 0.58 1.78
z_N_actor[3,1] 0.10 0.01 0.86 -1.63 -0.46 0.10 0.67 1.81
z_N_actor[3,2] 0.07 0.01 0.98 -1.84 -0.60 0.08 0.74 1.98
z_N_actor[3,3] -0.35 0.01 0.86 -2.02 -0.94 -0.37 0.22 1.38
z_N_actor[3,4] 0.02 0.01 0.86 -1.70 -0.55 0.01 0.58 1.73
z_N_actor[3,5] -0.05 0.01 0.85 -1.73 -0.62 -0.06 0.50 1.65
z_N_actor[3,6] -0.25 0.01 0.89 -1.97 -0.83 -0.26 0.31 1.56
z_N_actor[3,7] 0.50 0.01 0.97 -1.43 -0.13 0.50 1.16 2.38
L_Rho_actor[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00
L_Rho_actor[1,2] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_actor[1,3] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_actor[2,1] -0.07 0.00 0.32 -0.65 -0.30 -0.07 0.15 0.56
L_Rho_actor[2,2] 0.94 0.00 0.07 0.73 0.92 0.97 0.99 1.00
L_Rho_actor[2,3] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00
L_Rho_actor[3,1] 0.08 0.00 0.32 -0.55 -0.15 0.09 0.31 0.66
L_Rho_actor[3,2] -0.04 0.00 0.31 -0.64 -0.27 -0.05 0.18 0.57
L_Rho_actor[3,3] 0.88 0.00 0.10 0.61 0.83 0.91 0.96 1.00
a 0.24 0.01 0.66 -1.06 -0.19 0.24 0.67 1.56
bp 0.72 0.00 0.40 -0.14 0.47 0.73 0.98 1.48
bpc -0.03 0.00 0.44 -0.88 -0.31 -0.03 0.25 0.88
sigma_actor[1] 2.35 0.01 0.90 1.20 1.73 2.16 2.75 4.67
sigma_actor[2] 0.46 0.00 0.37 0.02 0.19 0.39 0.64 1.37
sigma_actor[3] 0.53 0.01 0.49 0.02 0.19 0.40 0.72 1.81
sigma_block[1] 0.23 0.00 0.20 0.01 0.09 0.18 0.31 0.74
sigma_block[2] 0.57 0.01 0.41 0.03 0.29 0.50 0.77 1.56
sigma_block[3] 0.52 0.01 0.43 0.02 0.20 0.42 0.72 1.59
a_block[1] -0.12 0.00 0.23 -0.68 -0.22 -0.06 0.01 0.23
a_block[2] 0.06 0.00 0.21 -0.32 -0.04 0.02 0.14 0.57
a_block[3] 0.10 0.00 0.22 -0.27 -0.02 0.04 0.19 0.65
a_block[4] -0.01 0.00 0.20 -0.44 -0.09 0.00 0.08 0.42
a_block[5] -0.02 0.00 0.20 -0.49 -0.11 -0.01 0.06 0.39
a_block[6] 0.00 0.00 0.22 -0.49 -0.09 0.00 0.10 0.46
bp_block[1] -0.18 0.00 0.42 -1.12 -0.42 -0.14 0.05 0.64
bp_block[2] -0.11 0.00 0.41 -0.99 -0.32 -0.07 0.11 0.70
bp_block[3] -0.23 0.00 0.43 -1.24 -0.46 -0.16 0.03 0.54
bp_block[4] 0.15 0.00 0.41 -0.59 -0.08 0.09 0.37 1.11
bp_block[5] 0.04 0.00 0.40 -0.75 -0.18 0.01 0.24 0.92
bp_block[6] 0.63 0.01 0.57 -0.14 0.17 0.53 0.96 1.98
bpc_block[1] -0.37 0.01 0.54 -1.75 -0.63 -0.22 -0.01 0.38
bpc_block[2] 0.18 0.00 0.44 -0.57 -0.05 0.09 0.39 1.28
bpc_block[3] 0.22 0.00 0.47 -0.56 -0.04 0.11 0.43 1.40
bpc_block[4] -0.08 0.00 0.45 -1.11 -0.28 -0.03 0.12 0.82
bpc_block[5] -0.07 0.00 0.42 -1.02 -0.26 -0.03 0.12 0.78
bpc_block[6] 0.09 0.00 0.48 -0.88 -0.13 0.04 0.30 1.19
Rho_block[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00
Rho_block[1,2] -0.06 0.00 0.32 -0.65 -0.29 -0.06 0.17 0.57
Rho_block[1,3] 0.04 0.00 0.32 -0.57 -0.19 0.04 0.27 0.63
Rho_block[2,1] -0.06 0.00 0.32 -0.65 -0.29 -0.06 0.17 0.57
Rho_block[2,2] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00
Rho_block[2,3] -0.04 0.00 0.31 -0.62 -0.27 -0.05 0.18 0.57
Rho_block[3,1] 0.04 0.00 0.32 -0.57 -0.19 0.04 0.27 0.63
Rho_block[3,2] -0.04 0.00 0.31 -0.62 -0.27 -0.05 0.18 0.57
Rho_block[3,3] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00
a_actor[1] -1.02 0.01 0.71 -2.43 -1.48 -1.01 -0.55 0.38
a_actor[2] 4.44 0.02 1.63 2.09 3.36 4.17 5.21 8.34
a_actor[3] -1.31 0.01 0.72 -2.75 -1.77 -1.30 -0.83 0.11
a_actor[4] -1.35 0.01 0.72 -2.80 -1.82 -1.34 -0.88 0.10
a_actor[5] -1.00 0.01 0.71 -2.42 -1.48 -0.99 -0.53 0.40
a_actor[6] 0.20 0.01 0.72 -1.24 -0.28 0.20 0.66 1.60
a_actor[7] 1.55 0.01 0.76 0.10 1.05 1.53 2.04 3.08
bp_actor[1] 0.05 0.00 0.37 -0.68 -0.13 0.02 0.22 0.89
bp_actor[2] 0.03 0.01 0.64 -1.21 -0.24 0.00 0.25 1.46
bp_actor[3] 0.22 0.00 0.42 -0.44 -0.02 0.12 0.41 1.25
bp_actor[4] 0.16 0.00 0.39 -0.52 -0.05 0.08 0.34 1.09
bp_actor[5] 0.10 0.00 0.38 -0.61 -0.09 0.04 0.26 0.99
bp_actor[6] -0.31 0.00 0.42 -1.35 -0.54 -0.21 -0.01 0.28
bp_actor[7] -0.04 0.00 0.43 -1.00 -0.23 -0.02 0.15 0.87
bpc_actor[1] 0.02 0.00 0.42 -0.92 -0.15 0.01 0.20 0.94
bpc_actor[2] 0.20 0.01 0.83 -1.18 -0.13 0.05 0.41 2.31
bpc_actor[3] -0.28 0.01 0.50 -1.58 -0.49 -0.14 0.02 0.46
bpc_actor[4] -0.05 0.00 0.43 -1.05 -0.22 -0.01 0.15 0.79
bpc_actor[5] -0.08 0.00 0.43 -1.13 -0.25 -0.02 0.12 0.73
bpc_actor[6] -0.14 0.00 0.45 -1.25 -0.32 -0.05 0.08 0.69
bpc_actor[7] 0.41 0.01 0.73 -0.41 -0.01 0.18 0.64 2.39
Rho_actor[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00
Rho_actor[1,2] -0.07 0.00 0.32 -0.65 -0.30 -0.07 0.15 0.56
Rho_actor[1,3] 0.08 0.00 0.32 -0.55 -0.15 0.09 0.31 0.66
Rho_actor[2,1] -0.07 0.00 0.32 -0.65 -0.30 -0.07 0.15 0.56
Rho_actor[2,2] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00
Rho_actor[2,3] -0.05 0.00 0.32 -0.63 -0.28 -0.05 0.17 0.56
Rho_actor[3,1] 0.08 0.00 0.32 -0.55 -0.15 0.09 0.31 0.66
Rho_actor[3,2] -0.05 0.00 0.32 -0.63 -0.28 -0.05 0.17 0.56
Rho_actor[3,3] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00
lp__ -285.47 0.11 6.46 -299.01 -289.56 -285.23 -281.02 -273.65
n_eff Rhat
z_N_block_id[1,1] 13367 1
z_N_block_id[1,2] 16316 1
z_N_block_id[1,3] 13212 1
z_N_block_id[1,4] 16245 1
z_N_block_id[1,5] 14391 1
z_N_block_id[1,6] 13216 1
z_N_block_id[2,1] 11937 1
z_N_block_id[2,2] 11867 1
z_N_block_id[2,3] 12192 1
z_N_block_id[2,4] 14644 1
z_N_block_id[2,5] 13497 1
z_N_block_id[2,6] 10467 1
z_N_block_id[3,1] 15608 1
z_N_block_id[3,2] 15577 1
z_N_block_id[3,3] 17322 1
z_N_block_id[3,4] 16464 1
z_N_block_id[3,5] 17740 1
z_N_block_id[3,6] 15742 1
L_Rho_block[1,1] NaN NaN
L_Rho_block[1,2] NaN NaN
L_Rho_block[1,3] NaN NaN
L_Rho_block[2,1] 13964 1
L_Rho_block[2,2] 6881 1
L_Rho_block[2,3] NaN NaN
L_Rho_block[3,1] 18184 1
L_Rho_block[3,2] 17024 1
L_Rho_block[3,3] 5530 1
z_N_actor[1,1] 3997 1
z_N_actor[1,2] 8100 1
z_N_actor[1,3] 4054 1
z_N_actor[1,4] 4042 1
z_N_actor[1,5] 4067 1
z_N_actor[1,6] 4812 1
z_N_actor[1,7] 5978 1
z_N_actor[2,1] 17688 1
z_N_actor[2,2] 19821 1
z_N_actor[2,3] 15620 1
z_N_actor[2,4] 15806 1
z_N_actor[2,5] 16515 1
z_N_actor[2,6] 13494 1
z_N_actor[2,7] 19772 1
z_N_actor[3,1] 16698 1
z_N_actor[3,2] 25570 1
z_N_actor[3,3] 15609 1
z_N_actor[3,4] 17747 1
z_N_actor[3,5] 16452 1
z_N_actor[3,6] 16474 1
z_N_actor[3,7] 17924 1
L_Rho_actor[1,1] NaN NaN
L_Rho_actor[1,2] NaN NaN
L_Rho_actor[1,3] NaN NaN
L_Rho_actor[2,1] 20181 1
L_Rho_actor[2,2] 5099 1
L_Rho_actor[2,3] NaN NaN
L_Rho_actor[3,1] 16979 1
L_Rho_actor[3,2] 16551 1
L_Rho_actor[3,3] 5465 1
a 4604 1
bp 9915 1
bpc 10895 1
sigma_actor[1] 4844 1
sigma_actor[2] 7378 1
sigma_actor[3] 6330 1
sigma_block[1] 7461 1
sigma_block[2] 5026 1
sigma_block[3] 6372 1
a_block[1] 11376 1
a_block[2] 14094 1
a_block[3] 11484 1
a_block[4] 14446 1
a_block[5] 12892 1
a_block[6] 12830 1
bp_block[1] 10766 1
bp_block[2] 11464 1
bp_block[3] 10088 1
bp_block[4] 10004 1
bp_block[5] 10791 1
bp_block[6] 6266 1
bpc_block[1] 9908 1
bpc_block[2] 11090 1
bpc_block[3] 10070 1
bpc_block[4] 12510 1
bpc_block[5] 12340 1
bpc_block[6] 11472 1
Rho_block[1,1] NaN NaN
Rho_block[1,2] 13964 1
Rho_block[1,3] 18184 1
Rho_block[2,1] 13964 1
Rho_block[2,2] 11984 1
Rho_block[2,3] 15006 1
Rho_block[3,1] 18184 1
Rho_block[3,2] 15006 1
Rho_block[3,3] 11786 1
a_actor[1] 4930 1
a_actor[2] 7208 1
a_actor[3] 4880 1
a_actor[4] 5074 1
a_actor[5] 4983 1
a_actor[6] 4827 1
a_actor[7] 5096 1
bp_actor[1] 12464 1
bp_actor[2] 14817 1
bp_actor[3] 10567 1
bp_actor[4] 12646 1
bp_actor[5] 13023 1
bp_actor[6] 10818 1
bp_actor[7] 14796 1
bpc_actor[1] 12189 1
bpc_actor[2] 12373 1
bpc_actor[3] 8575 1
bpc_actor[4] 11896 1
bpc_actor[5] 10873 1
bpc_actor[6] 10218 1
bpc_actor[7] 9055 1
Rho_actor[1,1] NaN NaN
Rho_actor[1,2] 20181 1
Rho_actor[1,3] 16979 1
Rho_actor[2,1] 20181 1
Rho_actor[2,2] 10875 1
Rho_actor[2,3] 14880 1
Rho_actor[3,1] 16979 1
Rho_actor[3,2] 14880 1
Rho_actor[3,3] 10080 1
lp__ 3172 1
"""