Table 4.
Nested models.
|
| ||||
|---|---|---|---|---|
| PARAMETER: | a (ACTION PRECISION) | cr (REWARD SENSITIVITY) | η (LEARNING RATE) | a0 (INSENSITIVITY TO INFORMATION) |
|
| ||||
| Default value if not estimated | 4 | (always estimated) | (removed from model) | 0.25 |
|
| ||||
| Prior means during estimation* | 4 | 4 | 0.5 | 0.25 |
|
| ||||
| Model 1 | Y | Y | N | N |
|
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| Model 2 | Y | Y | Y | N |
|
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| Model 3 | Y | Y | Y | Y |
|
| ||||
| Model 4 | N | Y | Y | Y |
|
| ||||
| Model 5 | N | Y | Y | N |
|
| ||||
| Model 6 | N | Y | N | N |
|
| ||||
| Model 7 | N | Y | N | Y |
|
| ||||
| Model 8 | Y | Y | N | Y |
|
| ||||
| Model 9** | Y | Y | Wins/Losses | Y |
|
| ||||
| Model 10 | Y | Y | Wins/Losses | N |
|
| ||||
Y indicates that a parameter was estimated for that model; N indicates that a parameter was not estimated for that model.
* Prior variance for all parameters was set to a precise value of 2–2 in order to deter over-fitting.
** Winning model.