Reformat pkgdown workflow

.Rbuildignore

@@ -21,3 +21,5 @@ vignettes/loo2-non-factorizable_cache/*
 
 ^CRAN-SUBMISSION$
 ^release-prep\.R$
+^_pkgdown\.yml$
+^pkgdown$

.github/workflows/pkgdown.yaml

@@ -0,0 +1,60 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  # build dev site on merged pushes
+  push:
+    branches: [main, master]
+  # build full site on releases
+  release:
+    types: [published]
+  workflow_dispatch:
+
+name: pkgdown.yaml
+
+concurrency:
+  group: pages
+  cancel-in-progress: true
+
+jobs:
+  pkgdown:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::pkgdown, local::., any::withr, stan-dev/pkgdown-config
+
+      # - uses: actions/cache@v4
+      #   with:
+      #     path: vignettes/**/_cache
+      #     key: knitr-${{ runner.os }}-${{ hashFiles('vignettes/**/*.Rmd') }}
+
+      - name: Build site
+        run: |
+          withr::with_envvar(
+            c("NOT_CRAN" = "true"), # this should already be set by setup-r@v2? keeping because vignettes don't build otherwise
+            pkgdown::build_site_github_pages(
+              lazy = FALSE, # change to TRUE if runner times out.
+              run_dont_run = TRUE,
+              new_process = TRUE
+            )
+          )
+        shell: Rscript {0}
+
+      - name: Deploy to GitHub pages 🚀
+        uses: JamesIves/github-pages-deploy-action@v4.5.0
+        with:
+          clean: false
+          branch: gh-pages
+          folder: docs

_pkgdown.yml

@@ -0,0 +1,129 @@
+url: https://mc-stan.org/loo/
+destination: "docs/"
+template:
+  package: pkgdownconfig
+development:
+  mode: auto
+
+navbar:
+  title: "loo"
+
+  structure:
+    left: [home, vignettes, functions, pkgs, news, stan]
+    right: [search, bluesky, twitter, forum, github, lightswitch]
+
+  components:
+    home:
+      icon: fa-home fa-lg
+      href: index.html
+    vignettes:
+      text: Vignettes
+      href: articles/index.html
+    functions:
+      text: Functions
+      href: reference/index.html
+    pkgs:
+      text: Other Packages
+      menu:
+        - text: rstan
+          href: https://mc-stan.org/rstan
+        - text: cmdstanr
+          href: https://mc-stan.org/cmdstanr
+        - text: rstanarm
+          href: https://mc-stan.org/rstanarm
+        - text: bayesplot
+          href: https://mc-stan.org/bayesplot
+        - text: shinystan
+          href: https://mc-stan.org/shinystan
+        - text: projpred
+          href: https://mc-stan.org/projpred
+        - text: rstantools
+          href: https://mc-stan.org/rstantools
+        - text: posterior
+          href: https://mc-stan.org/posterior
+
+articles:
+  - title: Getting started
+    desc: |
+      These vignettes demonstrate how to use the **loo** package to perform approximate leave-one-out cross-validation or exact K-fold cross-validation for Bayesian models fit using MCMC, compare models on estimated predictive performance on new data, and weight models for averaging predictive distributions.
+    contents:
+      - loo2-example
+      - loo2-weights
+      - loo2-with-rstan
+      - loo2-elpd
+  - title: Additional topics
+    desc: |
+      These vignettes demonstrate how to use the **loo** package for more complicated scenarios including models with non-factorized likelihoods, forecasting models, models fit to very large datasets, and more.
+    contents:
+      - loo2-non-factorized
+      - loo2-lfo
+      - loo2-large-data
+      - loo2-moment-matching
+      - loo2-mixis
+  - title: Frequently asked questions
+    contents:
+      - faq
+
+external-articles:
+  - name: faq
+    title: Cross-validation FAQ
+    description: Answers to frequently asked questions about cross-validation and the **loo** package (links to external site).
+    href: https://users.aalto.fi/~ave/CV-FAQ.html
+
+reference:
+  - title: Package description, glossary, and included data sets
+    contents:
+      - loo-package
+      - loo-glossary
+      - loo-datasets
+  - title: Approximate LOO-CV
+    desc: |
+      Approximate LOO-CV, Pareto smoothed importance sampling (PSIS), and diagnostics.
+    contents:
+      - loo
+      - loo_subsample
+      - loo_approximate_posterior
+      - loo_moment_match
+      - loo_moment_match_split
+      - E_loo
+      - psis
+      - ap_psis
+      - tis
+      - sis
+      - importance_sampling
+      - weights.importance_sampling
+      - pareto-k-diagnostic
+  - title: Model comparison weighting/averaging
+    desc: |
+      Functions for comparing models and computing model weights via stacking of predictive distributions or pseudo-BMA weighting.
+    contents:
+      - loo_compare
+      - loo_model_weights
+      - stacking_weights
+      - pseudobma_weights
+  - title: Helper functions for K-fold CV
+    contents:
+      - kfold_split_random
+      - kfold_split_stratified
+      - kfold_split_grouped
+      - kfold
+      - elpd
+  - title: Other functions
+    contents:
+      - loo_predictive_metric
+      - crps
+      - elpd
+      - waic
+      - extract_log_lik
+      - pointwise
+      - relative_eff
+      - gpdfit
+      - starts_with("example_loglik")
+      - print.loo
+      - nobs.psis_loo_ss
+      - obs_idx
+      - update.psis_loo_ss
+  - title: Deprecated functions
+    contents:
+      - compare
+      - psislw

pkgdown/favicon/site.webmanifest

@@ -0,0 +1,21 @@
+{
+  "name": "",
+  "short_name": "",
+  "icons": [
+    {
+      "src": "/web-app-manifest-192x192.png",
+      "sizes": "192x192",
+      "type": "image/png",
+      "purpose": "maskable"
+    },
+    {
+      "src": "/web-app-manifest-512x512.png",
+      "sizes": "512x512",
+      "type": "image/png",
+      "purpose": "maskable"
+    }
+  ],
+  "theme_color": "#ffffff",
+  "background_color": "#ffffff",
+  "display": "standalone"
+}

vignettes/loo2-moment-matching.Rmd

@@ -117,12 +117,20 @@ Next we fit the model in Stan using the __rstan__ package:
 data(roaches, package = "rstanarm")
 roaches$roach1 <- sqrt(roaches$roach1)
 y <- roaches$y
-x <- roaches[,c("roach1", "treatment", "senior")]
-offset <- log(roaches[,"exposure2"])
+x <- roaches[, c("roach1", "treatment", "senior")]
+offset <- log(roaches[, "exposure2"])
 n <- dim(x)[1]
 k <- dim(x)[2]
 
-standata <- list(N = n, K = k, x = as.matrix(x), y = y, offset = offset, beta_prior_scale = 2.5, alpha_prior_scale = 5.0)
+standata <- list(
+  N = n,
+  K = k,
+  x = as.matrix(x),
+  y = y,
+  offset = offset,
+  beta_prior_scale = 2.5,
+  alpha_prior_scale = 5.0
+)
 
 # Compile
 stanmodel <- stan_model(model_code = stancode)
@@ -239,7 +247,9 @@ __rstan__ objects, the functions look like this:
 .create_skeleton <- function(pars, dims) {
   out <- lapply(seq_along(pars), function(i) {
     len_dims <- length(dims[[i]])
-    if (len_dims < 1) return(0)
+    if (len_dims < 1) {
+      return(0)
+    }
     return(array(0, dim = dims[[i]]))
   })
   names(out) <- pars
@@ -254,7 +264,7 @@ post_draws_stanfit <- function(x, ...) {
 # compute a matrix of log-likelihood values for the ith observation
 # matrix contains information about the number of MCMC chains
 log_lik_i_stanfit <- function(x, i, parameter_name = "log_lik", ...) {
-  loo::extract_log_lik(x, parameter_name, merge_chains = FALSE)[, , i]
+  loo::extract_log_lik(x, parameter_name, merge_chains = FALSE)[,, i]
 }
 
 # transform parameters to the unconstraint space
@@ -272,13 +282,24 @@ unconstrain_pars_stanfit <- function(x, pars, ...) {
 
 # compute log_prob for each posterior draws on the unconstrained space
 log_prob_upars_stanfit <- function(x, upars, ...) {
-  apply(upars, 1, rstan::log_prob, object = x,
-        adjust_transform = TRUE, gradient = FALSE)
+  apply(
+    upars,
+    1,
+    rstan::log_prob,
+    object = x,
+    adjust_transform = TRUE,
+    gradient = FALSE
+  )
 }
 
 # compute log_lik values based on the unconstrained parameters
-log_lik_i_upars_stanfit <- function(x, upars, i, parameter_name = "log_lik",
-                                  ...) {
+log_lik_i_upars_stanfit <- function(
+  x,
+  upars,
+  i,
+  parameter_name = "log_lik",
+  ...
+) {
   S <- nrow(upars)
   out <- numeric(S)
   for (s in seq_len(S)) {

vignettes/loo2-non-factorized_cache/html/__packages

@@ -0,0 +1,6 @@
+knitr
+loo
+Rcpp
+brms
+bayesplot
+ggplot2