RBesT/_pkgdown.yml at main · Novartis/RBesT · GitHub

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url: https://opensource.nibr.com/RBesT/

# using katex as per comment here: https://github.com/r-lib/pkgdown/issues/2704#issuecomment-2307055568
# this is needed to get equations to work with pkgdown 2.1.1
# version following pkfdown 2.1.1 should not require these
# customizations any longer
template:
  bootstrap: 5
  includes:
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home:

# Function reference grouped along the typical RBesT workflow as
# illustrated in the "Getting started" (introduction) vignette:
# derive a prior (MAP) -> approximate & tune it -> evaluate the design
# -> analyse the trial. Lower-level building blocks and data follow.
reference:
  - title: Package overview
    contents:
      - RBesT-package

  - title: Prior derivation (Meta-Analytic-Predictive analysis)
    desc: >
      Combine historical data into a Meta-Analytic-Predictive (MAP)
      prior and inspect the model fit.
    contents:
      - gMAP
      - predict.gMAP
      - plot.gMAP
      - forest_plot
      - draws-RBesT
      - nsamples

  - title: Prior approximation
    desc: >
      Approximate MCMC samples (or any sample) by a parametric mixture
      of conjugate distributions.
    contents:
      - mixfit
      - automixfit
      - plot.EM

  - title: Effective sample size
    desc: Quantify the informativeness of a (mixture) prior.
    contents:
      - ess

  - title: Prior robustification
    desc: Make a prior robust against prior-data conflict.
    contents:
      - robustify

  - title: Design evaluation
    desc: >
      Define decision rules and evaluate operating characteristics and
      the probability of success for 1- and 2-sample designs.
    contents:
      - decision1S
      - decision2S
      - decision1S_boundary
      - decision2S_boundary
      - oc1S
      - oc2S
      - pos1S
      - pos2S

  - title: Trial analysis
    desc: >
      Conjugate posterior updating and predictive distributions used to
      analyse the actual trial outcome.
    contents:
      - postmix
      - preddist

  - title: Mixture distributions
    desc: Construct, combine and evaluate mixture distributions.
    contents:
      - mixbeta
      - mixgamma
      - mixnorm
      - mixmvnorm
      - mixcombine
      - mix
      - mixdiff
      - mixplot
      - likelihood

  - title: Interoperability and utilities
    desc: Read/write mixtures, use them in brms, and helper functions.
    contents:
      - mixstanvar
      - mixjson
      - lodds
      - BinaryExactCI

  - title: Datasets
    contents:
      - AS
      - asthma
      - colitis
      - crohn
      - transplant