Description Usage Arguments Details Value
This function graphs an agent's probability of choosing the same action in
State FC based on the prior trial's transition type (common or rare) as well
as whether the last trial was rewarded. This "stay probability" is calculated
according to a logistic regression model, predicting on the data from which
it was fit. This function checks whether the data has been pre-modeled,
meaning the logistic regression probabilities have already been calculated.
If so, this function just plots the probabilities. If not, this function
calls logSetup
, getLogFit
, getLogPreds
, and then plots
the data.
1 |
data |
The output of |
preModeled |
Logical: TRUE if the data has been passed through
|
dataType |
Should be a character string. Either "MF" if the simulation was purely model-free (x = 0) or "MB" if the simulation had model-based influence (x > 0). |
x |
If the parameter dataType is "MB", please enter the x used in generating simulation data. This will add more information to the plot, though it is unnecessary. |
alpha |
Logical: TRUE means the plot will be faceted by the learning rate alpha; false otherwise. Default is TRUE. |
gamma |
Logical: TRUE means the plot will be faceted by the temporal discount rate gamma; false otherwise. Default is TRUE. |
Please indicate whether the data was "MF" or "MB" (see parameter dataType) for plot title purposes. The plot can be faceted by learning rates and temporal discount terms (see parameters alpha and gamma).
A plot showing the stay probabilities for a given simulation/agent.
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