engine_ABC: The Engine of Approximate Bayesian Computation (ABC)

In multiRL: Reinforcement Learning Tools for Multi-Armed Bandit

The Engine of Approximate Bayesian Computation (ABC)

Description

Because abc::abc() requires summary statistics together with the corresponding input parameters, this function converts the generated simulated data into a standardized collection of summary statistics and input parameters, facilitating subsequent execution of abc::abc().

Usage

engine_ABC(
  data,
  colnames,
  behrule,
  model,
  funcs = NULL,
  priors,
  settings = NULL,
  control = control,
  ...
)

Arguments

data	A data frame in which each row represents a single trial, see data
colnames	Column names in the data frame, see colnames
behrule	The agent's implicitly formed internal rule, see behrule
model	Reinforcement Learning Model
funcs	The functions forming the reinforcement learning model, see funcs
priors	Prior probability density function of the free parameters, see priors
settings	Other model settings, see settings
control	Settings manage various aspects of the iterative process, see control
...	Additional arguments passed to internal functions.

Value

A List containing a DataFrame of the parameters used to generate the simulated data and the summary statistics for Approximate Bayesian Computation (ABC).

multiRL documentation built on March 31, 2026, 5:06 p.m.