StatisticalRethinkingJulia · rikhuijzer · Jan 8, 2021 · Jan 7, 2021 · Jan 7, 2021 · Jan 8, 2021
diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
@@ -23,18 +23,30 @@ jobs:
           version: 1 # Latest stable release, for example, `1.5.3`.
 
       - name: Build site
-        run: julia -e '
-          using Pkg; Pkg.add(["NodeJS", "Franklin"]);
-          using NodeJS; run(`$(npm_cmd()) install highlight.js`);
-          using Franklin;
-          Pkg.develop(path="."); Pkg.activate("."); Pkg.instantiate();
-          Franklin.optimize();
-          verify_links()' > build.log
+        run: |
+          julia -e '
+            using Pkg; Pkg.add(["NodeJS", "Franklin"]);
+            using NodeJS; run(`$(npm_cmd()) install highlight.js`);
+            using Franklin;
+            Pkg.develop(path="."); Pkg.activate("."); Pkg.instantiate();
+            Franklin.optimize();
+            verify_links()' > build.log;
+          cat build.log
 
       - name: Deploy to secondary branch
-        # Only deploy when pushed to master.
         if: ${{ github.event_name == 'push' }}
         uses: peaceiris/actions-gh-pages@v3
         with:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           publish_dir: ./__site
+
+      - name: Validate output
+        run: |
+          # A Franklin Warning means an error occurred when evaluating code.
+          if grep -1 "Franklin Warning" build.log; then
+            echo "Franklin reported a warning"
+            exit 1
+          else
+            echo "Franklin did not report a warning"
+          fi
+
diff --git a/Project.toml b/Project.toml
@@ -6,18 +6,24 @@ version = "1.1.3"
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Franklin = "713c75ef-9fc9-4b05-94a9-213340da978e"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 NodeJS = "2bd173c7-0d6d-553b-b6af-13a54713934c"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+RData = "df47a6cb-8c03-5eed-afd8-b6050d6c41da"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
 StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [compat]
 CSV = "0.8"
 DataFrames = "0.22"
+Distributions = "0.24"
 Franklin = "0.10"
 NodeJS = "1.1"
+RData = "0.7"
 StatsFuns = "0.9"
 StatsPlots = "0.14"
 Turing = "0.15"
-
diff --git a/_css/jtd.css b/_css/jtd.css
@@ -617,13 +617,15 @@ body { counter-reset: eqnum; }
   display: inline-block;
 } /* overwrite katex settings */
 
+/* Not interesting for this site.
 .katex-display::after {
   counter-increment: eqnum;
   content: "(" counter(eqnum) ")";
   position: relative;
   float: right;
   padding-right: 5px;
 }
+*/
 
 /* ==================================================================
     CODE & HIGHLIGHT.JS

diff --git a/index.md b/index.md
@@ -11,6 +11,8 @@ We have tried our best to let this site be without mistakes.
 However, if you find a mistake on this website, please let us know.
 The code for this website is available on [GitHub](https://github.com/StatisticalRethinkingJulia/TuringModels.jl).
 
+\toc
+
 ### About the pages
 
 Each page aims to contain all the code required to reproduce the results.

diff --git a/models.md b/models.md
@@ -21,7 +21,7 @@ Before you look at the models below, you might want to look at the [Basic Exampl
 - [m13.1](varying-intercepts-reedfrogs): Varying intercepts Reedfrogs
 - [m13.1](varying-slopes-cafe): Varying slopes cafes
 - [m13.2](multinomial-poisson): Multinomial Poisson regression
-- [m13.3](varying-intercepts-admission): Varying intercepts admission decisions [not-implemented]
+- [m13.3](varying-intercepts-admission): Varying intercepts admission decisions
 
 ## 1st Edition (2015)
 
@@ -31,15 +31,15 @@ Before you look at the models below, you might want to look at the [Basic Exampl
 - [m8.2](wild-chain): Wild chain
 - [m8.3](weakly-informative-priors): Weakly informative priors
 - [m8.4](non-identifiable): Non-identifiable model
-- [m10.3](chimpanzees): Chimpanzees [not-implemented]
-- [m10.4](estimate-handedness-chimpanzees): Estimate handedness for each Chimpanzee [not-implemented]
-- [m10.10](oceanic-tool-complexity): Oceanic tool complexity [not-implemented]
-- [m10.yyt](admit-reject): Admit or reject [not-implemented]
+- [m10.3](chimpanzees): Chimpanzees
+- [m10.4](estimate-handedness-chimpanzees): Estimate handedness for each Chimpanzee
+- [m10.10](oceanic-tool-complexity): Oceanic tool complexity
+- [m10.yyt](admit-reject): Admit or reject
 - [m11.5](beta-binomial): Beta-binomial
 - [m11.7](multinomial-poisson): Multinomial Poisson regression
 - [m12.1](varying-intercepts-reedfrogs): Varying intercepts Reedfrogs
 - [m13.4](ignoring-gender-admit): Ignoring gender for admittance
-- [m13.6](multivariate-chimpanzees-priors): Multivariate Chimpanzees priors [not-implemented]
-- [m13.6nc](non-centered-chimpanzees): Non-centered Chimpanzees [not-implemented]
-- [m13.7](spatial-autocorrelation-oceanic): Spatial autocorrelation in Oceanic tools [not-implemented]
+- [m13.6](multivariate-chimpanzees-priors): Multivariate Chimpanzees priors
+- [m13.6nc](non-centered-chimpanzees): Non-centered Chimpanzees
+- [m13.7](spatial-autocorrelation-oceanic): Spatial autocorrelation in Oceanic tools
 - [m14.1](varying-slopes-cafe): Varying slopes cafes
diff --git a/models/admit-reject.md b/models/admit-reject.md
@@ -1,37 +1,6 @@
 +++
 title = "Admit or reject"
+showall = true
 +++
 
-```
-using TuringModels, StatsFuns
-
-delim = ';'
-d = CSV.read(joinpath(@__DIR__, "..", "..", "data", "UCBadmit.csv"), DataFrame; delim);
-size(d) # Should be 12x5
-
-@model m_pois(admit, reject) = begin
-   α₁ ~ Normal(0,100)
-   α₂ ~ Normal(0,100)
-
-   for i ∈ 1:length(admit)
-       λₐ = exp(α₁)
-       λᵣ = exp(α₂)
-       admit[i] ~ Poisson(λₐ)
-       reject[i] ~ Poisson(λᵣ)
-   end
-end;
-
-chns = sample(m_pois(d[:, :admit], d[:, :reject]), Turing.NUTS(0.65), 1000);
-
-# Rethinking/CmdStan result
-
-m_10_yyt_result = "
-    mean   sd 5.5% 94.5% n_eff Rhat
- a1 4.99 0.02 4.95  5.02  2201    1
- a2 5.44 0.02 5.41  5.47  2468    1
-";
-
-# Describe the draws
-
-chns |> display
-```
+\literate{/scripts/admit-reject.jl}
diff --git a/models/beta-binomial.md b/models/beta-binomial.md
@@ -1,13 +1,15 @@
 +++
 title = "Beta-binomial"
+showall = true
 +++
 
-In Rethinking 2nd Edition, this model is defined as 
+This beta-binomial model is `m11.5` in Statistical Rethinking 1st Edition.
+In Statistical Rethinking 2nd Edition it is `m12.1` and defined as 
 
 $$
 \begin{aligned}
   A_i &\sim \text{BetaBinomial}(N_i, \overline{p}_i, \theta) \\
-  \text{logit}(\overline{p}_i) &= \alpha_\text{GID}[i] \\
+  \text{logit}(\overline{p}_i) &= \alpha_{\text{GID}[i]} \\
   \alpha_j &\sim \text{Normal}(0, 1.5) \\
   \theta &= \phi + 2 \\
   \phi &\sim \text{Exponential(1)}
@@ -16,58 +18,5 @@ $$
 
 \toc 
 
-## Data
+\literate{/scripts/beta-binomial.jl}
 
-```julia:data
-using DataFrames
-using TuringModels # hide
-
-import CSV
-
-data_path = joinpath(TuringModels.project_root, "data", "UCBadmit.csv")
-df = CSV.read(data_path, DataFrame; delim=';')
-
-@assert size(df) == (12, 5) # hide
-write_csv(name, data) = CSV.write(joinpath(@OUTPUT, "$name.csv"), data) # hide
-write_csv("data", df) # hide
-```
-\output{data}
-
-\tableinput{}{./code/output/data.csv}
-
-## Model
-```julia:model
-using StatsFuns: logistic
-using Turing
-
-@model function m11_5(admit, applications)
-  θ ~ truncated(Exponential(1), 0, Inf)
-  α ~ Normal(0, 2)
-
-  # alpha and beta for the BetaBinomial must be provided.
-  # The two parameterizations are related by
-  # alpha = prob * theta, and beta = (1-prob) * theta.
-  # See https://github.com/rmcelreath/rethinking/blob/master/man/dbetabinom.Rd
-
-  prob = logistic(α)
-  alpha = prob * θ
-  beta = (1 - prob) * θ
-  admit .~ BetaBinomial.(applications, alpha, beta)
-end
-
-model = m11_5(df.admit, df.applications)
-chains = sample(model, NUTS(0.65), 1000)
-```
-\output{model}
-
-## Output
-
-\defaultoutput{}
-
-## Original output
-
-```
-        mean   sd  5.5% 94.5% n_eff Rhat
-theta   2.74 0.96  1.43  4.37  3583    1
-a       -0.37 0.31 -0.87  0.12  3210    1
-```
diff --git a/models/chimpanzees.md b/models/chimpanzees.md
@@ -1,39 +1,10 @@
 +++
 title = "Chimpanzees"
+showall = true
 +++
 
-```
-using TuringModels, StatsFuns
+This is the third Chimpanzees model (`m10.3`) in Statistical Rethinking Edition 1.
 
-delim=';'
-d = CSV.read(joinpath(@__DIR__, "..", "..", "data", "chimpanzees.csv"), DataFrame; delim);
-size(d) # Should be 504x8
+\toc
 
-# pulled_left, condition, prosoc_left
-@model m10_3(y, x₁, x₂) = begin
-    α ~ Normal(0, 10)
-    βp ~ Normal(0, 10)
-    βpC ~ Normal(0, 10)
-
-    logits = α .+ (βp .+ βpC * x₁) .* x₂
-    y .~ BinomialLogit.(1, logits)
-end;
-
-chns = sample(m10_3(d[:,:pulled_left], d[:,:condition], d[:,:prosoc_left]),
-  Turing.NUTS(0.65), 2000);
-
-# Rethinking result
-
-m_10_03t_result = "
-      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
-";
-
-# Describe the draws
-
-chns |> display
-
-# End of m10.03t.jl
-```
+\literate{/scripts/chimpanzees.jl}
diff --git a/models/estimate-handedness-chimpanzees.md b/models/estimate-handedness-chimpanzees.md
@@ -1,53 +1,11 @@
 +++
 title = "Estimate handedness for each Chimpanzee"
+showall = true
 +++
 
-```
-using TuringModels, StatsFuns
+This is model `m10.4` in Statistical Rethinking Edition 1.
 
-delim=';'
-d = CSV.read(joinpath(@__DIR__, "..", "..", "data", "chimpanzees.csv"), DataFrame; delim);
-size(d) # Should be 504x8
+\toc
 
-# pulled_left, actors, condition, prosoc_left
-@model m10_4(y, actors, x₁, x₂) = begin
-    # Number of unique actors in the data set
-    N_actor = length(unique(actors))
+\literate{/scripts/estimate-handedness-chimpanzees.jl}
 
-    # Set an TArray for the priors/param
-    α ~ filldist(Normal(0, 10), N_actor)
-    βp ~ Normal(0, 10)
-    βpC ~ Normal(0, 10)
-
-    logits = α[actors] .+ (βp .+ βpC * x₁) .* x₂
-    y .~ BinomialLogit.(1, logits)
-end;
-
-chns = sample(m10_4(d[:,:pulled_left], d[:,:actor],d[:,:condition],
-  d[:,:prosoc_left]), Turing.NUTS(0.65), 1000);
-
-# Rethinking/CmdStan results
-
-m_10_04s_result = "
-Iterations = 1:1000
-Thinning interval = 1
-Chains = 1,2,3,4
-Samples per chain = 1000
-
-Empirical Posterior Estimates:
-        Mean        SD       Naive SE       MCSE      ESS
-a.1 -0.74503184 0.26613979 0.0042080396 0.0060183398 1000
-a.2 10.77955494 5.32538998 0.0842018089 0.1269148045 1000
-a.3 -1.04982353 0.28535997 0.0045119373 0.0049074219 1000
-a.4 -1.04898135 0.28129307 0.0044476339 0.0056325117 1000
-a.5 -0.74390933 0.26949936 0.0042611590 0.0052178124 1000
-a.6  0.21599365 0.26307574 0.0041595927 0.0045153523 1000
-a.7  1.81090866 0.39318577 0.0062168129 0.0071483527 1000
-bp  0.83979926 0.26284676 0.0041559722 0.0059795826 1000
-bpC -0.12913322 0.29935741 0.0047332562 0.0049519863 1000
-";
-
-# Describe the draws
-
-chns |> display
-```
diff --git a/models/ignoring-gender-admit.md b/models/ignoring-gender-admit.md
@@ -1,7 +1,6 @@
 +++
 title = "Ignoring gender for admittance"
 showall = true
-reeval = true
 +++
 
 \literate{/scripts/ignoring-gender-admit.jl}