rpl_e: Step 4: Replaying the experiment with optimal parameters

Description

Step 4: Replaying the experiment with optimal parameters

Usage

rpl_e(
  result,
  free_params = NULL,
  data,
  colnames,
  behrule,
  ids = NULL,
  models,
  funcs = NULL,
  priors = NULL,
  settings = NULL,
  ...
)

Value

An S3 object of class multiRL.replay. A List containing, for each subject and each fitted model, the estimated optimal parameters, along with the resulting

multiRL.model and multiRL.summary objects obtained by replaying the model with those parameters.

Arguments

result: Result from rcv_d or fit_p
free_params: In order to prevent ambiguity regarding the free parameters, their names can be explicitly defined by the user.
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
ids: The Subject ID of the participant whose data needs to be fitted.
models: Reinforcement Learning Models
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
...: Additional arguments passed to internal functions.

Example

 # info
 data = multiRL::TAB
 colnames = list(
   object = c("L_choice", "R_choice"), 
   reward = c("L_reward", "R_reward"),
   action = "Sub_Choose"
 )
 behrule = list(
   cue = c("A", "B", "C", "D"),
   rsp = c("A", "B", "C", "D")
 )
 
 replay.recovery <- multiRL::rpl_e(
   result = recovery.MLE,
  
   data = data,
   colnames = colnames,
   behrule = behrule,
  
   models = list(multiRL::TD, multiRL::RSTD, multiRL::Utility),
   settings = list(name = c("TD", "RSTD", "Utility")),
  
   omit = c("data", "funcs")
 )
 replay.fitting <- multiRL::rpl_e(
   result = fitting.MLE,
  
   data = data,
   colnames = colnames,
   behrule = behrule,
  
   models = list(multiRL::TD, multiRL::RSTD, multiRL::Utility),
   settings = list(name = c("TD", "RSTD", "Utility")),
  
   omit = c("funcs")
 )