R: Toolbox for Error-Driven Learning Simulations with Two-Layer Networks

# Toolbox for Error-Driven Learning Simulations with Two-Layer Networks

## Documentation for package ‘edl’ version 1.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

activationsCueSet | Calculate the change in activation for a specific cue or set of cues.
activationsEvents | Calculate the activations for each learning event.
activationsMatrix | Calculate the activations for one or a set of cues.
activationsOutcomes | Calculate the activations for all outcomes in the data.
check | Remove empty cues and/or outcomes.
checkWM | Check whether cues and outcomes exist in a weight matrix and optionally add.
createTrainingData | Create event training data from a frequency data frame.
createWM | Create empty weight matrix based on a set of cues and outcomes.
cueWindow | Create a 'cue window', for overlapping or continuous cues.
dat | Simulated learning data.
edl | Toolbox for Error-Driven Learning Simulations with Two-Layer Networks
getActivations | Function to calculate the activations.
getCues | Extract cues from list of weightmatrices.
getLambda | Retrieve the lambda values for all or specific outcomes for each learning event.
getOutcomes | Extract outcomes from list of weightmatrices.
getUpdate | Retrieve the weight updates and their change for each learning event.
getValues | Retrieve all cues from a vector of text strings.
getWeightsByCue | Extract the change of connection weights between a specific cue and all outcomes.
getWeightsByOutcome | Extract the change of connection weights between all cues and a specific outcome.
getWM | Retrieve all cues from a vector of text strings.
luceChoice | Function implementing the Luce choice rule.
plotActivations | Visualize the change of connection weights between a specific outcome and all cues.
plotCueWeights | Visualize the change of connection weights between a specific cue and all outcomes.
plotNetwork | Return strong weights.
plotOutcomeWeights | Visualize the change of connection weights between a specific outcome and all cues.
RWlearning | Function implementing the Rescorla-Wagner learning.
RWlearningMatrix | Function implementing the Rescorla-Wagner learning.
RWlearningNoCueCompetition | Function implementing the Rescorla-Wagner learning equations without cue competition (for illustration purposes).
RWlearningNoOutcomeCompetition | Function implementing the Rescorla-Wagner learning equetions without outcome competition (for illustration purposes).
setBackground | Set value background cue.
updateWeights | Function implementing the Rescorla-Wagner learning for a single learning event.
updateWeightsNoCueCompetition | Function implementing the Rescorla-Wagner learning equations without cue competition for a single learning event.
updateWeightsNoOutcomeCompetition | Function implementing the Rescorla-Wagner learning equations without outcome competition (for illustration purposes) for a single learning event.