A python package for binary risky choice modeling for 4 models: 

* Expected Utility Theory: $U = p*A^\alpha$
* Risk-Return: $U = EV - b*Var$ 
* Coefficient of Variation: $U = EV - b*CV$ where $CV = \sqrt{Var}/EV1$ 
* Hyperbolic: $U = A/(1+h*\theta)$ where $\theta = (1-p)/p$

where $A$ is the payoff amount, $p$ is the probability of winning that outcome, $EV$ is Expected value ($Ap$), 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==0.1.9
>>> 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