simple_model_wrapper: Simple wrapper for integrate testing
In gjcooper/gcphd-model_of_dce: Models of Consumer Choice Experiments

simple_model_wrapper

R Documentation

Simple wrapper for integrate testing

This function does the parameter transformations necessary for the model to run.

simple_model_wrapper(rt, A, b_acc, b_rej, t0, drifts, accept, model)

simple_model_wrapper(rt, A, b_acc, b_rej, t0, drifts, accept, model)

`rt`	A vector of response times
`A`	Start point variability
`b_acc`	positive evidence threshold
`b_rej`	negative evidence threshold
`t0`	non decision time parameter
`drifts`	An array of drift rates, 4 x length(rt) with the columns being vectors of drift rates for accept price, reject price, accept rating, reject rating respectively
`accept`	Whether we are looking at accept or reject trials
`model`	The loglikelihood function currently being tested

The log of the likelihood for the rt's for the parameters from the model

The vector x should contain the following elements: A number of \alpha values

A - the start point variability
b^a and b^r, the thresholds to either accept or reject the item.
t0 - the residual time, bounded above by the minimum response time for the participant
12 drift rates. For each attribute there are three stimulus levels. For each of these 6 attribute levels there are two drift rates, one drift rate to accept (v^a) and one to reject (v^r)

The vector x should contain the following elements: A number of \alpha values

A - the start point variability
b^a and b^r, the thresholds to either accept or reject the item.
t0 - the residual time, bounded above by the minimum response time for the participant
12 drift rates. For each attribute there are three stimulus levels. For each of these 6 attribute levels there are two drift rates, one drift rate to accept (v^a) and one to reject (v^r)