docs: update ecosystem inventory and syntax pointers

README.md

@@ -3,9 +3,10 @@
 Source for the [EpiAware](https://github.com/EpiAware) organisation website — the
 meta-site for a composable Julia ecosystem for infectious disease modelling.
 
-The site links out to the ecosystem's packages, wraps their documentation in a
-single browser, and hosts org-level material (using Julia, FAQ, contributing,
-developer, funding, getting involved) alongside a gallery and team page.
+The site is the ecosystem's shared front door: an inventory of every package
+linking out to its own documentation, the approaches that tie them together,
+and org-level material (using Julia, FAQ, contributing, developer, funding,
+getting involved) alongside a gallery and team page.
 
 ## Build
 
@@ -22,19 +23,23 @@ Pushes to `main` deploy it to GitHub Pages.
 
 ## Adding a package
 
-Copy `packages/_template.qmd` to `packages/<yourpackage>.qmd`, fill in the front
-matter and body, and open a pull request. The card on the
-[Packages](https://epiaware.github.io/packages/) page is generated from the file,
-and adding the package to the docs browser is a one-line entry in the
-`EPIAWARE_DOCS` list in `docs.qmd`.
+Add a row to the table in `packages/index.qmd`: package name linking to its
+documentation, a GitHub icon linking to its source, a status pill, a
+`data-category` (`modelling`, `distributions`, or `infrastructure`) so it
+picks up the category filter, and a one-sentence description. Open a pull
+request.
 
 ## Structure
 
 - `index.qmd` — home
-- `packages/` — one page per package, plus the generated listing and a template
-- `docs.qmd` — unified documentation browser
-- `tutorials.qmd`, `gallery.qmd`, `team.qmd`, `funding.qmd`, `get-involved.qmd`, `community.qmd`
+- `packages/index.qmd` — the ecosystem inventory (one filterable table)
+- `approaches/` — the modelling approaches (composed distributions, composable
+  Turing models) and their shared overview
+- `tutorials/index.qmd` — a filterable listing of runnable tutorials, each
+  living in its own package's documentation
+- `gallery.qmd`, `team.qmd`, `funding.qmd`, `get-involved.qmd`, `community.qmd`
 - `using-julia.qmd`, `faq.qmd`, `contributing.qmd`, `developer.qmd` — org-level guides
+- `news/` — blog posts
 - `theme-light.scss`, `theme-dark.scss`, `styles.css` — theme
 - `assets/img/logo.svg` — org logo
 

approaches/composed-distributions.qmd

@@ -79,9 +79,9 @@ using ComposedDistributions, Distributions
 
 # BDBV-inspired delay tree: parallel pathways
 # with sequential, resolve, and compete nested together
-tree = compose((
+tree = @uncertain compose((
     clinical = sequential(
-        :onset_admit => Gamma(1.2, 3.0),
+        :onset_admit => Gamma(Normal(1.2, 0.2), 3.0),
         :admit_resolve => resolve(
             :death => (Gamma(2.0, 3.5), 0.3),
             :discharge => (Gamma(1.0, 8.0), 0.7))),
@@ -121,10 +121,10 @@ Both share one internal representation, so the model you build to simulate is th
 
 The approach is built in four layers, each resting on the one before.
 
-- **Leaves** are any Distributions.jl `UnivariateDistribution`, used directly as the per-event delays.
+- **Leaves** are any Distributions.jl `UnivariateDistribution`, used directly as the per-event delays, including Distributions.jl's own `truncated(...)` and `censored(...)` wrappers — a leaf can be truncated or censored, but wrapping a whole tree the same way errors by design, since the composers read a wrapper's structure to peel through to the free delay underneath.
 - **Composers** wire named leaves into an event tree.
 - **Combination and lowering** join or collapse whole delays with `convolved`, `difference`, and `observed_distribution`.
-- **Parameters and edits** read and reshape an assembled tree with `params_table`, `param_priors`, `update`, `prune`, and `splice`.
+- **Parameters and edits** read and reshape an assembled tree with `params_table`, `param_priors`, `uncertain`, `update`, `prune`, and `splice`.
 
 ### Five composers
 
@@ -151,15 +151,17 @@ The model does not change, only the delays each case supplies.
 
 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.
-[ModifiedDistributions.jl](https://modifieddistributions.epiaware.org/) supplies modifier leaves that rescale, weight, or transform a delay.
+[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.
 
 ### Uncertainty in the parameters themselves
 
 A delay taken from the literature rarely comes with exact parameters.
-`uncertain` wraps a leaf whose parameters are themselves distributions, nested to any depth.
+`uncertain` wraps a leaf whose parameters are themselves distributions, nested to any depth, and the `@uncertain` macro reads a distribution passed as a constructor argument as that parameter's prior, so `@uncertain Gamma(Normal(2.0, 0.3), 1.0)` reads the same as writing it out by hand.
 The result is still a univariate distribution, so it composes as a leaf everywhere, and `has_uncertain` guards against forgetting to pin it down before fitting.
 
+`uncertain` is also the verb for promoting parameters on a tree already built: `uncertain(tree; onset_admit = (shape = prior,))` targets one parameter, and bare `uncertain(tree)` promotes every free parameter with a default prior in one call.
+
 ### One representation across the workflow
 
 The tree is not tied to one package or one use.
@@ -169,7 +171,8 @@ There is no translation step between the delay model, the infection model, and t
 ### Read the posterior back through the same tree
 
 After fitting, the posterior is read back by applying the parameter draws to the same tree.
-`update(template, chain)` walks each draw through the tree and returns a distribution per draw, so every delay mean, convolution, or contrast comes from the fitted object itself.
+`update(template, chain)` reduces the chain to a point summary and returns one fitted tree; `update(template, table)` does the same from a Tables.jl table of values or priors, for a bulk edit outside a sampling loop.
+Reading every draw rather than a point summary maps `update` over `param_draws(template, chain)`, so every delay mean, convolution, or contrast still comes from the fitted object itself, one draw at a time.
 Nothing is recomputed in separate post-processing that could drift from the model.
 
 ## Where next
@@ -179,13 +182,23 @@ Nothing is recomputed in separate post-processing that could drift from the mode
   [composing distributions](https://composeddistributions.epiaware.org/dev/getting-started/tutorials/composing-distributions).
 - The [ComposedDistributions.jl documentation](https://composeddistributions.epiaware.org/dev/)
   covers the full API and worked examples.
-- [ConvolvedDistributions.jl](https://convolveddistributions.epiaware.org/) handles
+- [ConvolvedDistributions.jl](https://convolveddistributions.epiaware.org/dev/) handles
   the convolutions (sums) of delays that arise naturally in event trees.
-- [ModifiedDistributions.jl](https://modifieddistributions.epiaware.org/) lets you
+- [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
   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.
 - Ready to fit a full model with infection dynamics? See the
   [composable Turing models approach](composable-turing-models.qmd).
 

developer.qmd

@@ -41,7 +41,7 @@ Packages run a consistent set of quality tools:
 - [JET.jl](https://github.com/aviatesk/JET.jl) for static analysis (`@report_opt`, `@report_package`)
 - Doctests and formatting checks
 
-[EpiAwarePackageTools.jl](https://epiawarepackagetools.epiaware.org/) provides the shared
+[EpiAwarePackageTools.jl](https://epiawarepackagetools.epiaware.org/dev/) provides the shared
 harnesses, including automatic-differentiation tests across backends.
 
 ## Checking performance

faq.qmd

@@ -54,7 +54,7 @@ version. Package-specific citation details live in each package's documentation.
 
 ## Where do I get help or report a bug?
 
-- Questions: the [epinowcast forum](https://community.epinowcast.org/) or a package's GitHub Discussions
+- Questions: the [epinowcast forum](https://community.epinowcast.org/)
 - Bugs and feature requests: open an issue on the relevant GitHub repository
 - General Julia help: [Julia Discourse](https://discourse.julialang.org/) and [Slack](https://julialang.org/slack/)
 

get-involved.qmd

@@ -12,7 +12,8 @@ ecosystem, there is a place for you here.
 - **Discuss.** Join the [epinowcast forum](https://community.epinowcast.org/) to
   ask questions and talk through ideas — the best first step.
 - **Try the packages.** Use them on a real problem and tell us what worked and
-  what didn't, via a package's GitHub Discussions or issues.
+  what didn't, via the [forum](https://community.epinowcast.org/) or a
+  package's GitHub issues.
 - **Contribute.** Fix a bug, improve documentation, or add a feature. See the
   [Contributing](contributing.qmd) guide.
 - **Bring a use case.** If you have a modelling problem that composable tools

index.qmd

@@ -146,9 +146,9 @@ using ComposedDistributions, Distributions
 
 # BDBV-inspired delay tree: parallel pathways
 # with sequential, resolve, and compete nested together
-tree = compose((
+tree = @uncertain compose((
     clinical = sequential(
-        :onset_admit => Gamma(1.2, 3.0),
+        :onset_admit => Gamma(Normal(1.2, 0.2), 3.0),
         :admit_resolve => resolve(
             :death => (Gamma(2.0, 3.5), 0.3),
             :discharge => (Gamma(1.0, 8.0), 0.7))),

packages/index.qmd

@@ -60,7 +60,7 @@ Status reflects where a package sits in its release cycle rather than a judgemen
       <td class="data-name">
         <a href="https://convolveddistributions.epiaware.org/dev/">ConvolvedDistributions.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/ConvolvedDistributions.jl" aria-label="ConvolvedDistributions.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>Convolve probability distributions, with shared numerical quadrature.</td>
     </tr>
@@ -74,25 +74,33 @@ Status reflects where a package sits in its release cycle rather than a judgemen
     </tr>
     <tr data-category="distributions">
       <td class="data-name">
-        <a href="https://github.com/EpiAware/LoweredDistributions.jl">LoweredDistributions.jl</a>
+        <a href="https://lowereddistributions.epiaware.org/dev/">LoweredDistributions.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/LoweredDistributions.jl" aria-label="LoweredDistributions.jl on GitHub"><i class="bi bi-github"></i></a>
-        <span class="status-pill status-experimental">in development</span>
+        <span class="status-pill status-experimental">experimental</span>
+      </td>
+      <td>Lower a distribution, or a whole composed event tree, onto a backend-agnostic dynamical-systems representation (a phase-type chain or a CTMC), then hand it to Catalyst, SciML, AlgebraicPetri, or JumpProcesses.</td>
+    </tr>
+    <tr data-category="distributions">
+      <td class="data-name">
+        <a href="https://github.com/EpiAware/DistributionsInference.jl">DistributionsInference.jl</a>
+        <a class="data-gh" href="https://github.com/EpiAware/DistributionsInference.jl" aria-label="DistributionsInference.jl on GitHub"><i class="bi bi-github"></i></a>
+        <span class="status-pill status-experimental">experimental</span>
       </td>
-      <td>Common components for differential equation infectious disease models. In development, so there is nothing to install yet.</td>
+      <td>A PPL-neutral fit protocol and log-density engine: any object that names its own parameters becomes fittable, with Turing.jl, Bijectors, and FlexiChains readback layered on as extensions rather than requirements.</td>
     </tr>
     <tr data-category="infrastructure">
       <td class="data-name">
-        <a href="https://epiawarepackagetools.epiaware.org/">EpiAwarePackageTools.jl</a>
+        <a href="https://epiawarepackagetools.epiaware.org/dev/">EpiAwarePackageTools.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/EpiAwarePackageTools.jl" aria-label="EpiAwarePackageTools.jl on GitHub"><i class="bi bi-github"></i></a>
         <span class="status-pill status-experimental">experimental</span>
       </td>
       <td>Shared scaffolding, quality checks, and test utilities used across the ecosystem.</td>
     </tr>
     <tr data-category="infrastructure">
       <td class="data-name">
-        <a href="https://github.com/EpiAware/EpiAwareADTools.jl">EpiAwareADTools.jl</a>
+        <a href="https://epiawareadtools.epiaware.org/dev/">EpiAwareADTools.jl</a>
         <a class="data-gh" href="https://github.com/EpiAware/EpiAwareADTools.jl" aria-label="EpiAwareADTools.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>Automatic differentiation safety machinery for the stack, tested across ForwardDiff, ReverseDiff, Mooncake, and Enzyme. Deliberately framed as fixes we host while we try to fix things upstream.</td>
     </tr>

tutorials/index.qmd

@@ -109,25 +109,25 @@ If you are new to an approach, start with the tutorial marked *start here*.
     </tr>
     <tr data-category="delays">
       <td class="data-name">
-        <a href="https://censoreddistributions.epiaware.org/dev/getting-started/tutorials/fitting-with-turing">Fitting with Turing</a>
+        <a href="https://censoreddistributions.epiaware.org/stable/getting-started/tutorials/fitting-with-turing">Fitting with Turing</a>
       </td>
       <td>Estimating a delay distribution from censored, truncated line-list data. <em>CensoredDistributions</em></td>
     </tr>
     <tr data-category="delays">
       <td class="data-name">
-        <a href="https://censoreddistributions.epiaware.org/dev/getting-started/tutorials/analytical-primarycensored-cdfs">Analytical primary-censored CDFs</a>
+        <a href="https://censoreddistributions.epiaware.org/stable/getting-started/tutorials/analytical-primarycensored-cdfs">Analytical primary-censored CDFs</a>
       </td>
       <td>Closed-form primary-event censoring, and when it beats numerical integration. <em>CensoredDistributions</em></td>
     </tr>
     <tr data-category="delays">
       <td class="data-name">
-        <a href="https://censoreddistributions.epiaware.org/dev/getting-started/tutorials/exponentially-tilted-primary-events">Exponentially tilted primary events</a>
+        <a href="https://censoreddistributions.epiaware.org/stable/getting-started/tutorials/exponentially-tilted-primary-events">Exponentially tilted primary events</a>
       </td>
       <td>Primary events that are not uniform within their window, as in a growing epidemic. <em>CensoredDistributions</em></td>
     </tr>
     <tr data-category="delays">
       <td class="data-name">
-        <a href="https://censoreddistributions.epiaware.org/dev/getting-started/tutorials/ad-backends">Automatic differentiation backends</a>
+        <a href="https://censoreddistributions.epiaware.org/stable/getting-started/tutorials/ad-backends">Automatic differentiation backends</a>
       </td>
       <td>Which AD backend to use for censored delay likelihoods, and what it costs. <em>CensoredDistributions</em></td>
     </tr>