multiRL (version 0.2.3)

engine_ABC: 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,
  ...
)

Value

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

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.