bayesplot/_pkgdown.yml at master · stan-dev/bayesplot · GitHub

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url: https://mc-stan.org/bayesplot

development:
  mode: auto

destination: "."

template:
  package: pkgdownconfig

navbar:
  title: "bayesplot"

  structure:
    left: [home, vignettes, functions, news, pkgs, stan]
    right: [search, bluesky, forum, github, lightswitch]

  components:
    pkgs:
      text: Other Packages
      menu:
        - text: cmdstanr
          href: https://mc-stan.org/cmdstanr
        - text: loo
          href: https://mc-stan.org/loo
        - text: posterior
          href: https://mc-stan.org/posterior
        - text: projpred
          href: https://mc-stan.org/projpred
        - text: rstan
          href: https://mc-stan.org/rstan
        - text: rstanarm
          href: https://mc-stan.org/rstanarm
        - text: rstantools
          href: https://mc-stan.org/rstantools
        - text: shinystan
          href: https://mc-stan.org/shinystan

articles:
  - title: "Getting Started"
    desc: >
      These vignettes provide an introduction to visualizing MCMC draws and
      diagnostics and performing graphical posterior predictive checks using
      the **bayesplot** package.
    contents:
      - plotting-mcmc-draws
      - visual-mcmc-diagnostics
      - graphical-ppcs

reference:
  - title: "Overview"
    desc: >
      Package overview
    contents:
      - bayesplot-package
  - title: "Aesthetics"
    desc: >
      Functions for setting the color scheme and ggplot theme used
      by **bayesplot**. (Also see the separate **ggplot helpers** section
      below.)
    contents:
      - bayesplot-colors
      - bayesplot_theme_get
      - theme_default
  - title: "PPC"
    desc: >
      Functions for carrying out a wide variety of graphical model checks
      based on comparing observed data to draws from the posterior or prior
      predictive distribution.
    contents:
      - PPC-overview
      - starts_with("ppc")
      - pp_check
  - title: "PPD"
    desc: >
      Functions for creating graphical displays of simulated data from the
      posterior or prior predictive distribution (PPD). These plots are essentially
      the same as the corresponding PPC plots but without comparing to any observed
      data.
    contents:
      - PPD-overview
      - starts_with("ppd")
  - title: "MCMC"
    desc: >
      Functions for creating plots of MCMC draws of model parameters and
      general MCMC diagnostics.
    contents:
      - MCMC-overview
      - MCMC-diagnostics
      - MCMC-distributions
      - MCMC-intervals
      - MCMC-recover
      - MCMC-scatterplots
      - MCMC-parcoord
      - MCMC-traces
      - MCMC-combos
  - title: "HMC/NUTS diagnostics"
    desc: >
      Functions for plotting diagnostics specific to Hamiltonian Monte Carlo (HMC)
      and the No-U-Turn Sampler (NUTS). Some of the general MCMC plotting functions
      (`mcmc_parcoord()`, `mcmc_pairs()`, `mcmc_scatter()`, `mcmc_trace()`) can also
      show HMC/NUTS diagnostic information if optional arguments are specified,
      but the special functions below are _only_ intended for use with HMC/NUTS.
    contents:
      - MCMC-nuts
  - title: "Tidy parameter selection for MCMC plots"
    desc: >
      Helper functions for tidy parameter selection and examples of using
      **bayesplot** with [**dplyr**](https://dplyr.tidyverse.org/).
    contents:
      - tidy-params
  - title: "ggplot helpers"
    desc: >
      Convenience functions for arranging multiple plots, adding features
      to plots, and shortcuts for modifying individual ggplot theme elements.
    contents:
      - bayesplot_grid
      - bayesplot-helpers
  - title: "Extractors"
    desc: >
      Functions extracting various quantities needed for plotting from different
      types of fitted model objects.
    contents:
      - bayesplot-extractors
  - title: "Miscellaneous"
    desc: >
      Functions for generating data for examples and listing available
      plotting functions.
    contents:
      - example-data
      - available_ppc