mle_twochoiceRL: Maximum-likelihood estimation (MLE) of behavior in a...

In psuthaharan/twochoiceRL: Modeling Behavior for Two-Choice Decisions

Description

This function runs the MLE technique to recover behavior in a two-choice decision task.

Usage

mle_twochoiceRL(
  data = NULL,
  param = list(init_x1, init_x2),
  fn = "mle.objectiveFunction",
  opt = "TRM",
  radius = c(tr_rad[1], tr_rad[2]),
  nRes = nRes,
  progress_bar = progress_bar
)

Arguments

data	simulated two-choice task data
param	randomly generated initial parameters
fn	objective function being minimized
opt	optimization algorithm used. Defaults to trust-region method (trm)
radius	starting and maximum allowed trust region radius. Defaults to 1 and 5.
nRes	number of restarts. Defaults to 5
progress_bar	tracks completion time of function. Defaults to TRUE.

Value

A list containing the sum log-likelihood, mle estimates of parameter 1 per subject, mle estimates of parameter 2 per subject, laplace values of parameter 1 per subject, laplace values of parameter 2 per subject.

psuthaharan/twochoiceRL documentation built on Dec. 22, 2021, 9:56 a.m.