From 66b128cabd547401337978218af7dd3a927b74a4 Mon Sep 17 00:00:00 2001
From: Ray Kim <msca8h@naver.com>
Date: Thu, 16 Nov 2023 03:08:37 +0000
Subject: [PATCH] remove redundant example directory

---
 examples/gibbs/Project.toml |   5 --
 examples/gibbs/main.jl      | 120 ------------------------------------
 2 files changed, 125 deletions(-)
 delete mode 100644 examples/gibbs/Project.toml
 delete mode 100644 examples/gibbs/main.jl

diff --git a/examples/gibbs/Project.toml b/examples/gibbs/Project.toml
deleted file mode 100644
index 3b79938..0000000
--- a/examples/gibbs/Project.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[deps]
-Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-MCMCTesting = "9963b6a1-5d46-439c-8efc-3a487843c7fa"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
diff --git a/examples/gibbs/main.jl b/examples/gibbs/main.jl
deleted file mode 100644
index c9b4713..0000000
--- a/examples/gibbs/main.jl
+++ /dev/null
@@ -1,120 +0,0 @@
-
-"""
-  Example in Section 4 of Gandy and Scott 2021.
-"""
-
-using MCMCTesting
-using Random
-using Statistics
-using Distributions
-
-struct Model
-    sigma    ::Float64
-    sigma_eps::Float64
-end
-
-struct GibbsRandScan end
-
-struct GibbsRandScanWrongMean end
-
-struct GibbsRandScanWrongVar end
-
-function MCMCTesting.sample_predictive(rng::Random.AbstractRNG, model::Model, θ)
-    # y ∼ θ₁ + θ₂ + ϵ
-    rand(rng, Normal(θ[1] + θ[2], model.sigma_eps))
-end
-
-function MCMCTesting.sample_joint(rng::Random.AbstractRNG, model::Model)
-    θ₁ = rand(rng, Normal(0, model.sigma))
-    θ₂ = rand(rng, Normal(0, model.sigma))
-    θ  = [θ₁, θ₂]
-    y  = MCMCTesting.sample_predictive(rng, model, θ)
-    θ, y
-end
-
-function complete_conditional(θ::Real, σ²::Real, σ²_ϵ::Real, y::Real)
-    μ = σ²/(σ²_ϵ + σ²)*(y - θ)
-    σ = 1/sqrt(1/σ²_ϵ + 1/σ²)
-    Normal(μ, σ)
-end
-
-function complete_conditional_wrongmean(θ::Real, σ²::Real, σ²_ϵ::Real, y::Real)
-    μ = σ²/(σ²_ϵ + σ²)*(y + θ)
-    σ = 1/sqrt(1/σ²_ϵ + 1/σ²)
-    Normal(μ, σ)
-end
-
-function complete_conditional_wrongvar(θ::Real, σ²::Real, σ²_ϵ::Real, y::Real)
-    μ = σ²/(σ²_ϵ + σ²)*(y - θ)
-    Normal(μ, sqrt(σ²))
-end
-
-function MCMCTesting.markovchain_transition(
-    rng::Random.AbstractRNG, model::Model, kernel::GibbsRandScan, θ, y
-)
-    θ    = copy(θ)
-    σ²   = model.sigma^2
-    σ²_ϵ = model.sigma_eps^2
-
-    if rand(Bernoulli(0.5))
-        θ[1] = rand(rng, complete_conditional(θ[2], σ², σ²_ϵ, y))
-        θ[2] = rand(rng, complete_conditional(θ[1], σ², σ²_ϵ, y))
-    else
-        θ[2] = rand(rng, complete_conditional(θ[1], σ², σ²_ϵ, y))
-        θ[1] = rand(rng, complete_conditional(θ[2], σ², σ²_ϵ, y))
-    end
-    θ
-end
-
-function MCMCTesting.markovchain_transition(
-    rng::Random.AbstractRNG, model::Model, kernel::GibbsRandScanWrongMean, θ, y
-)
-    θ    = copy(θ)
-    σ²   = model.sigma^2
-    σ²_ϵ = model.sigma_eps^2
-
-    if rand(Bernoulli(0.5))
-        θ[1] = rand(rng, complete_conditional_wrongmean(θ[2], σ², σ²_ϵ, y))
-        θ[2] = rand(rng, complete_conditional(          θ[1], σ², σ²_ϵ, y))
-    else
-        θ[2] = rand(rng, complete_conditional_wrongmean(θ[1], σ², σ²_ϵ, y))
-        θ[1] = rand(rng, complete_conditional(          θ[2], σ², σ²_ϵ, y))
-    end
-    θ
-end
-
-function MCMCTesting.markovchain_transition(
-    rng::Random.AbstractRNG, model::Model, kernel::GibbsRandScanWrongVar, θ, y
-)
-    θ    = copy(θ)
-    σ²   = model.sigma^2
-    σ²_ϵ = model.sigma_eps^2
-
-    if rand(Bernoulli(0.5))
-        θ[1] = rand(rng, complete_conditional_wrongvar(θ[2], σ², σ²_ϵ, y))
-        θ[2] = rand(rng, complete_conditional(         θ[1], σ², σ²_ϵ, y))
-    else
-        θ[2] = rand(rng, complete_conditional_wrongvar(θ[1], σ², σ²_ϵ, y))
-        θ[1] = rand(rng, complete_conditional(         θ[2], σ², σ²_ϵ, y))
-    end
-    θ
-end
-
-function main()
-    model = Model(sqrt(10), sqrt(0.1))
-
-    for test in [
-        TwoSampleTest(     100, 100),
-        TwoSampleGibbsTest(100, 100),
-        ExactRankTest(     100, 100),
-        ]
-        @info(test)
-        mcmctest(test, TestSubject(model, GibbsRandScan())) |> display
-        mcmctest(test, TestSubject(model, GibbsRandScanWrongMean())) |> display
-        mcmctest(test, TestSubject(model, GibbsRandScanWrongVar())) |> display
-        
-        seqmcmctest(test, TestSubject(model, GibbsRandScan()),          0.001, 32) |> display
-        seqmcmctest(test, TestSubject(model, GibbsRandScanWrongMean()), 0.001, 32) |> display
-        seqmcmctest(test, TestSubject(model, GibbsRandScanWrongVar()),  0.001, 32) |> display
-    end
-end