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All functions

ConfidenceOrientation
Confidence and response time data
LogLikRM()
Log-Likelihood functions for the independent and partially anti-correlated race models of confidence
LogLikWEV()
Log-Likelihood functions for the dynWEV and 2DSD models of confidence
PDFtoQuantiles() CDFtoQuantiles()
Get Quantiles from vectors of PDF or CDF values
dIRM() dIRM2() dPCRM() rIRM() rPCRM()
Independent and partially anti-correlated Race Model for Decision Confidence
d2DSD() r2DSD()
Pleskac and Busemeyer's 2DSD Model for Decision Confidence
dDDConf() rDDConf()
Drift Diffusion Model with time-dependent confidence
dynConfiR-package
The dynConfiR Package
dWEV() ddynaViTE() rdynaViTE() rWEV()
Dynamical visibility, time, and evidence model (dynaViTE) and Dynamical weighted evidence and visibility model (dynWEV)
fitRTConf()
Function for fitting sequential sampling confidence models
fitRTConfModels()
Function for fitting several sequential sampling confidence models in parallel
predictDDConf_Conf() predictDDConf_RT()
Prediction of Confidence Rating and Reaction Time Distribution in the drift diffusion confidence model
predictRM_Conf() predictRM_RT()
Prediction of Confidence Rating and Reaction Time Distribution in race models of confidence
predictConf() predictRT()
Prediction of confidence rating and response time distribution for sequential sampling confidence models
predictConfModels() predictRTModels()
Prediction of confidence and RT distributions for several sequential sampling confidence models and parameter constellations in parallel
predictWEV_Conf() predictWEV_RT()
Prediction of Confidence Rating and Response Time Distribution in dynaViTE, dynWEV, and 2DSD confidence models
rLCA()
Simulation of confidence ratings and RTs in leaky competing accumulator model
simulateRM() rRM_Kiani()
Simulation of confidence ratings and RTs in race confidence models
simulateRTConf()
Simulation of confidence ratings and RTs in sequential sampling confidence models
simulateWEV()
Simulation of confidence ratings and RTs in dynWEV and 2DSD confidence models