A python package for binary risky choice modeling for 4 models: 
    1. Expected Utility Theory: U = p * A^alpha 
    2. Risk-Return: U = EV - b * Var 
    3. Coefficient of Variation: U = EV - b *CV where CV = = sqrt(Var)/EV1 
    4. Hyperbolic: U = A/(1+h*theta) where theta = (1-p)/p 
where A is the payoff, p is the probability of winning that outcome, EV is Expected value (A*p), and Var is variance (P*(A-EV)**2 + (1 - P)*(-EV) ** 2) 

The package takes risky choice data (probability, payoffs, and decisions) of 2 options as inputs and returns a util-rc object that stores the estimated parameters, inverse temperature, fit metrics, model type, and number of observations in an instance variable named params.

To use the package,copy the following code into your terminal:
pip install util-rc==0.1.4
python3
from src.util_rc.main import util_rc
example = util_rc("E",[0,0,1],[10,10,10],[1,1,1],[20,30,40],[.6,.5,.4])
example.params

Dependencies: numpy version >= 1.26.4, scipy version >= 1.12.0