compute_BF_Stan: Sample and compute BF for various models using Stan

In lgaborini/rstanBF: rstanBF computes the Bayes Factor for data in specified two-level hierarchical models

Description

Sample and compute BF for various models using Stan.

Usage

compute_BF_Stan(
  data,
  model,
  hyperpriors,
  n.iter = 1000,
  n.burnin = 200,
  n.chains = 1,
  n.cores = 1,
  data_other = NULL,
  silent = FALSE,
  ...
)

Arguments

data	a list containing mtx, idx.ref, idx.quest
model	the model shortname (e.g. 'DirDir', 'DirFNorm')
hyperpriors	a list containing hyperparameter definitions
n.iter	number of HMC iterations (default: 1000)
n.burnin	number of HMC burn-in iterations (default: 200)
n.chains	number of HMC chains (default: 1)
n.cores	number of cores to use for HMC and bridge sampling (default: 1)
data_other	a list containing additional data for H_1 and H_2 models (default: NULL)
silent	if TRUE, do not print any progress
...	list of additional parameters to pass to rstan::sampling() method

Details

Two-sample model:

• samples are stored as matrix mtx

• reference items are indexed in mtx by idx.ref

• questioned items are indexed in mtx by idx.quest

• other items, non indexed, are discarded.

Hypotheses:

• H_1: samples in idx.ref and idx.quest come from the same source

• H_2: samples in idx.ref and idx.quest come from different sources

Return a stanBF object with these properties:

• model_name

• stanmodel (named list of Stan models)

• stanfit (named list of stanfit objects)

• stanbridge (named list of bridgesampler objects)

• BF (a double: the Bayes Factor)

For Dirichlet likelihoods, the returned object is a stanBF_turn, inheriting from stanBF. These objects contain also:

• df_samples (data.frame with posterior samples)

• custom plot methods

The object contains methods to plot and to extract samples.

Value

a stanBF object

lgaborini/rstanBF documentation built on March 10, 2021, 1:12 p.m.