docs: refresh package status and fix the composable Turing models approach example

approaches/composable-turing-models.qmd

@@ -75,28 +75,28 @@ page-layout: full
 :::
 
 ```{.julia .code-overflow-scroll}
-using ComposableTuringIDModels, Distributions, Turing
-
-# Renewal infections with an inline prior model
-data = IDData(gen_distribution = Gamma(1.4, 1 / 0.38))
-
-model = IDModel(
-    Renewal(data;
-        rt = AR(; ϵ_t = HierarchicalNormal(
-            std_prior = HalfNormal(0.1))),
-        initialisation_prior = Normal(log(1.0), 1.0)),
-
-    # Multiple observation layers:
-    #   delay → ascertainment → negative-binomial noise
-    LatentDelay(
-        Ascertainment(
-            NegativeBinomialError(),
-            Intercept(Normal(log(0.4), 0.1))),
-        truncated(Normal(5.0, 2.0), 0.0, Inf)))
-
-# Fit to case data with Turing's NUTS
+using ComposableTuringIDModels, Distributions, Turing, Mooncake
+using ADTypes: AutoMooncake
+
+# Renewal infections with an autoregressive log-R_t prior
+renewal = Renewal(;
+    generation_time = Gamma(1.4, 1 / 0.38),
+    rt = AR(; ϵ_t = HierarchicalNormal(std = HalfNormal(0.1))),
+    initialisation = Normal(log(1.0), 1.0))
+
+# Observation layers: delay → ascertainment → negative-binomial noise
+obs = LatentDelay(
+    Ascertainment(
+        NegativeBinomialError(),
+        Intercept(Normal(log(0.4), 0.1))),
+    truncated(Normal(5.0, 2.0), 0.0, Inf))
+
+model = IDModel(renewal, obs)
+
+# Fit to case data with Turing's NUTS (Mooncake AD)
 chain = sample(as_turing_model(model, cases, length(cases)),
-               NUTS(), MCMCThreads(), 1_000, 2)
+    NUTS(0.95; adtype = AutoMooncake(; config = nothing)),
+    MCMCThreads(), 100, 2)
 ```
 
 :::

approaches/composed-distributions.qmd

@@ -150,7 +150,7 @@ The model does not change, only the delays each case supplies.
 ### Censoring and modifiers compose as leaves
 
 Real line-list delays are rarely clean, and the corrections are part of the model rather than a preprocessing step.
-[CensoredDistributions.jl](https://censoreddistributions.epiaware.org/) supplies censoring leaves for primary-event censoring, interval censoring, and truncation.
+[CensoredDistributions.jl](https://censoreddistributions.epiaware.org/dev/) supplies censoring leaves for primary-event censoring, interval censoring, and truncation.
 [ModifiedDistributions.jl](https://modifieddistributions.epiaware.org/dev/) supplies modifier leaves that rescale, weight, or transform a delay.
 Both are leaves like any other, so they slot into the tree and the composers peel through them to reach the free delay underneath.
 
@@ -187,18 +187,14 @@ Nothing is recomputed in separate post-processing that could drift from the mode
 - [ModifiedDistributions.jl](https://modifieddistributions.epiaware.org/dev/) lets you
   rescale, weight, or otherwise transform individual leaves without changing the
   tree structure.
-- [CensoredDistributions.jl](https://censoreddistributions.epiaware.org/) adds
+- [CensoredDistributions.jl](https://censoreddistributions.epiaware.org/dev/) adds
   the censoring layer for real line-list data.
 - [LoweredDistributions.jl](https://lowereddistributions.epiaware.org/dev/) lowers
   the same tree onto a phase-type chain or a CTMC, the bridge to compartmental
   models.
-- Fitting outside Turing, or fitting a plain struct alongside a tree?
-  [DistributionsInference.jl](https://github.com/EpiAware/DistributionsInference.jl)
-  hosts the PPL-neutral log-density and readback that `as_logdensity` and
-  `as_turing` build on: `distribution_priors` assembles priors the same way
-  `param_priors` does for a tree, and `distribution_params` reads a fitted
-  chain back to the estimated values by name, whatever fittable object it
-  came from.
+- [DistributionsInference.jl](https://github.com/EpiAware/DistributionsInference.jl)
+  assembles PPL-neutral priors and reads a fitted chain back by name, for
+  fitting the tree (or any fittable struct) outside Turing.
 - Ready to fit a full model with infection dynamics? See the
   [composable Turing models approach](composable-turing-models.qmd).
 

packages/index.qmd

@@ -36,7 +36,7 @@ Status reflects where a package sits in its release cycle rather than a judgemen
       <td class="data-name">
         <a href="https://composableturingidmodels.epiaware.org/dev/">ComposableTuringIDModels.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/ComposableTuringIDModels.jl" aria-label="ComposableTuringIDModels.jl on GitHub"><i class="bi bi-github"></i></a>
-        <span class="status-pill status-experimental">experimental</span>
+        <span class="status-pill status-maturing">maturing</span>
       </td>
       <td>Assemble infectious disease models from interchangeable infection and observation parts as a single Turing model. The package that ties the ecosystem together.</td>
     </tr>
@@ -46,13 +46,13 @@ Status reflects where a package sits in its release cycle rather than a judgemen
         <a class="data-gh" href="https://github.com/EpiAware/CensoredDistributions.jl" aria-label="CensoredDistributions.jl on GitHub"><i class="bi bi-github"></i></a>
         <span class="status-pill status-maturing">maturing</span>
       </td>
-      <td>Handle the interval censoring and truncation biases common in epidemiological delay data, wrapping any Distributions.jl distribution.</td>
+      <td>Handle the interval censoring and truncation biases common in epidemiological delay data, wrapping any Distributions.jl distribution, and convolve series of censored delays with <code>convolve_series</code>.</td>
     </tr>
     <tr data-category="distributions">
       <td class="data-name">
         <a href="https://composeddistributions.epiaware.org/dev/">ComposedDistributions.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/ComposedDistributions.jl" aria-label="ComposedDistributions.jl on GitHub"><i class="bi bi-github"></i></a>
-        <span class="status-pill status-experimental">experimental</span>
+        <span class="status-pill status-maturing">maturing</span>
       </td>
       <td>Join the delays in a case's history into a single distribution that can simulate a case or be fitted to observed ones.</td>
     </tr>
@@ -72,6 +72,14 @@ Status reflects where a package sits in its release cycle rather than a judgemen
       </td>
       <td>Rescale, weight, modify hazards, or transform a distribution, while keeping the full Distributions.jl interface.</td>
     </tr>
+    <tr data-category="distributions">
+      <td class="data-name">
+        <a href="https://reparameteriseddistributions.epiaware.org/dev/">ReparameterisedDistributions.jl</a>
+        <a class="data-gh" href="https://github.com/EpiAware/ReparameterisedDistributions.jl" aria-label="ReparameterisedDistributions.jl on GitHub"><i class="bi bi-github"></i></a>
+        <span class="status-pill status-maturing">maturing</span>
+      </td>
+      <td>Express the same distribution under a different, equivalent parameterisation, so a model can be fitted in whatever form is most convenient and read back in your own.</td>
+    </tr>
     <tr data-category="distributions">
       <td class="data-name">
         <a href="https://lowereddistributions.epiaware.org/dev/">LoweredDistributions.jl</a>