Duplicate the approach of demonstrating the delayed choice tasks, for risky choice. This primarily aimed at creating a figure for the paper to demonstrate the method works well for risky choice.
Prerequisites:
[x] implement Du, Green & Myerson (2002) design procedure, #66
[x] decide on the true (data generating model), as either Linear-in-Log-Odds (#46), or Prelec 2 parameter version (#44), or other. (DECISION: going to use the LinearInLogOdds model as the true model.)
[ ] resolve #54 first, so that we have the summary stats of all params
[ ] update the parameter recovery code to work with 2 parameter situations (darc_parameter_recovery.py)
Duplicate the approach of demonstrating the delayed choice tasks, for risky choice. This primarily aimed at creating a figure for the paper to demonstrate the method works well for risky choice.
Prerequisites:
LinearInLogOddsmodel as the true model.)darc_parameter_recovery.py)