multiRL (version 0.2.3)

process_1_input: multiRL.input

Description

multiRL.input

Usage

process_1_input(
  data,
  colnames = list(),
  funcs = list(),
  params = list(),
  priors,
  settings = list(),
  ...
)

Value

An S4 object of class multiRL.input.

data

A DataFrame containing the trial-level raw data.

colnames

An S4 object of class multiRL.colnames, specifying the column names used in the input data.

features

An S4 object of class multiRL.features, containing standardized representations of states and actions transformed from the raw data.

params

An S4 object of class multiRL.params, containing model parameters.

priors

A List specifying prior distributions for free parameters.

funcs

An S4 object of class multiRL.funcs, containing functions used in model.

settings

An S4 object of class multiRL.settings, storing global settings for model estimation.

elements

A int indicating the number of elements within states.

subid

A Character string identifying the subject.

n_block

A int value indicating the number of blocks.

n_trial

A int value indicating the number of trials.

n_rows

A int value indicating the number of rows in the data.

extra

A List containing additional user-defined information.

Arguments

data

A data frame in which each row represents a single trial, see data

colnames

Column names in the data frame, see colnames

funcs

The functions forming the reinforcement learning model, see funcs

params

Parameters used by the model’s internal functions, see params

priors

Prior probability density function of the free parameters, see priors

settings

Other model settings, see settings

...

Additional arguments passed to internal functions.