dmcFitSubjectDE: dmcFitSubjectDE

In igmmgi/DMCfun: Diffusion Model of Conflict (DMC) in Reaction Time Tasks

dmcFitSubjectDE

Description

Fit theoretical data generated from dmcSim to observed data by minimizing the root-mean-square error (RMSE) between a weighted combination of the CAF and CDF functions using the R-package DEoptim. Alternative cost functions include squared percentage error ("SPE"), and g-squared statistic ("GS").

Usage

dmcFitSubjectDE(
  resOb,
  nTrl = 1e+05,
  minVals = list(),
  maxVals = list(),
  fixedFit = list(),
  freeCombined = list(),
  nCAF = 5,
  nDelta = 19,
  pDelta = vector(),
  tDelta = 1,
  deltaErrors = FALSE,
  costFunction = "RMSE",
  spDist = 1,
  drOnset = 0,
  drDist = 0,
  drShape = 3,
  drLim = c(0.1, 0.7),
  rtMax = 5000,
  subjects = c(),
  deControl = list(),
  numCores = 2
)

Arguments

resOb	Observed data (see flankerData and simonTask for data format)
nTrl	The number of trials to use within dmcSim.
minVals	Minimum values for the to-be estimated parameters. This is a list with values specified individually for amp, tau, drc, bnds, resMean, resSD, aaShape, spShape, sigm (e.g., minVals = list(amp = 10, tau = 5, drc = 0.1, bnds = 20, resMean = 200, resSD = 5, aaShape = 1, spShape = 2, spBias = -20, sigm = 1, bndsRate=0, bndsSaturation=0)).
maxVals	Maximum values for the to-be estimated parameters. This is a list with values specified individually for amp, tau, drc, bnds, resMean, resSD, aaShape, spShape, sigm (e.g., maxVals = list(amp = 40, tau = 300, drc = 1.0, bnds = 150, bndsRate=1, bndsSaturation=500, resMean = 800, resSD = 100, aaShape = 3, spShape = 4, spBias = 20, sigm = 10))
fixedFit	Fix parameter to starting value. This is a list with bool values specified individually for amp, tau, drc, bnds, resMean, resSD, aaShape, spShape, sigm (e.g., fixedFit = list(amp = F, tau = F, drc = F, bnds = F, bndsRate=T, bndsSaturation=T, resMean = F, resSD = F, aaShape = F, spShape = F, spBias = T, sigm = T, bndsRate=T, bndsSaturation=T)) NB. Value if fixed at midpoint between minVals and maxVals.
freeCombined	If fitting 2+ datasets at once, which parameters are allowed to vary between both fits (default = all parameters fixed between the two fits e.g. parameter = F). This is a list with bool values specified individually for amp, tau, drc, bnds, resMean, resSD, aaShape, spShape, spBias, sigm (e.g., freeCombined = list(amp = F, tau = F, drc = F, bnds = F, bndsRate=F, bndsSaturation=F, resMean = F, resSD = F, aaShape = F, spShape = F, spBias = F, sigm = F))
nCAF	The number of CAF bins.
nDelta	The number of delta bins.
pDelta	An alternative option to nDelta (tDelta = 1 only) by directly specifying required percentile values (vector of values 0-100)
tDelta	The type of delta calculation (1=direct percentiles points, 2=percentile bounds (tile) averaging)
deltaErrors	TRUE/FALSE Calculate delta bins for error trials
costFunction	The cost function to minimise: root mean square error ("RMSE": default), squared percentage error ("SPE"), or likelihood-ratio chi-square statistic ("GS")
spDist	The starting point distribution (0 = constant, 1 = beta, 2 = uniform)
drOnset	The starting point of controlled drift rate (i.e., "target" information) relative to automatic ("distractor" incormation) (> 0 ms)
drDist	The drift rate (dr) distribution type (0 = constant, 1 = beta, 2 = uniform)
drShape	The drift rate (dr) shape parameter
drLim	The drift rate (dr) range
rtMax	The limit on simulated RT (decision + non-decisional components)
subjects	NULL (aggregated data across all subjects) or integer for subject number
deControl	Additional control parameters passed to DEoptim (see DEoptim.control)
numCores	Number of cores to use

Value

dmcFitSubjectDE returns a list of objects of class "dmcfit"

Examples

# Code below can exceed CRAN check time limit, hence donttest
# Example 1: Flanker data from Ulrich et al. (2015)
fit <- dmcFitSubjectDE(flankerData, nTrl = 1000, subjects = c(1, 2), deControl = list(itermax=30))
plot(fit, flankerData, subject = 1)
plot(fit, flankerData, subject = 2)
summary(fit)

igmmgi/DMCfun documentation built on Nov. 22, 2024, 4:07 a.m.