Man pages for mcplR
Multiple Cue Probability Learning in R

AICcCorrected Akaike Information Criterion
ALCOVEAttention Learning COVEring map model (ALCOVE)
ALCOVElearningAttention Learning COVEring map model (ALCOVE)
canRepar-methodsReparametrization methods
ConstraintsList-classParameter constraints
fit-methodsFit a model (estimate model parameters).
GaussianMixtureResponseGenerate a Gaussian Mixture Response model
GaussianMixtureResponse-classClass "GaussianMixtureResponse"
GaussianResponse-classClass "GaussianResponse"
gcmGeneralized Context Model
ggcmgeneralized Generalized Context Model
GlmResponseGenerate a Generalized Linear Model (GLM) Response model
GlmResponse-classClass "GlmResponse"
MaxResponseMaximising responses with error
MaxResponse-classClass "MaxResponse"
McplBaseModelClass "McplBaseModel"
McplModelMcplModel
McplModel-classClass "McplModel"
mcplRmcplR: Multiple Cue Probability Learning models in R
mcplr-internalmcplR internal functions, methods and classes.
ParStructParameter structure objects
ParStruct-classClass "ParStruct"
RatioRuleResponse-classClass "RatioRuleResponse"
rescorlaWagnerRescorla-Wagner Model
RsqR-Squared
runm-methodsRun a model over the data.
simulatesimulate
slfnSingle Layer Feedforward Network
SMPTStock Market Prediction Task
WPTWeather Prediction Task data
mcplR documentation built on May 31, 2017, 1:49 a.m.