sim {qmvs}

Simulation of the queueing model of visual search

Description

sim.ny simulates a data set containing the responses and response times on either target present or target absent trials under specified set size level in an experiment using standard visual search paradigm, whereby the non-decision time for yes and no options are represented by two different parameters.

Usage

sim.ny(par, esterrorpar, c, k, pr, N, empRT, seed=0)

Arguments

par

A vector of length 3 or 4, equals (miat, mst, Tres) if non-decision time is assumed to be the same for no and yes responses (as in WM, WMdiffresp and WMdiffrespweight) and (miat, mst, Tresn, Tresy) otherwise (as in WMdiffrespshift and WMdiffrespshiftweight).

esterrorpar

A vector of length 5. Estimates of the accuracy-related parameters (\alpha, \beta, a_1, a_2, b)

c

A natural number representing the number of parallel servers of the system.

k

A natural number representing the total number of stimuli in the display (set size).

pr

Logical. If pr is TRUE, the function simulates data on target present trials; if pr is FALSE, it simulates data on target absent trials.

N

A natural number representing the number of simulation runs.

empRT

A vector of empirical response times collected under given target presence and set size condition.

seed

The random seed used in the simulation.

Value

A N \times 2 matrix. The first column contains the simulated response times and the second colum the corresponding simulated responses.

Author(s)

Yiq Li, [e-mail],https://www.xing.com/profile/Yiqi_Li3, Martin Schlather,[e-mail],https://www.wim.uni-mannheim.de/schlather/

References

Li, Yiqi (2020) Visual search as a queueing process. Doctoral dissertation, University of Mannheim.

See Also

queue

Examples

sim.ny(par = c(30, 200, 250, 350),
       esterrorpar = c(-2.67, 0.0094, 0.0299, 0.0020, 1.13),
       c = 4,
       k = 12,
       pr = TRUE, 
       N = 10000, seed = 0)