## models.pit()


Probability integral transform of each outcome under the family's


Usage


``` python
models.pit(
    family,
    y,
    mu,
    dispersion=1.0,
    weights=None,
    seed=0,
    theta=None,
    power=None
)
```


predictive distribution, randomized where it has atoms (counts, a Tweedie's zero); uniform when the model is calibrated.


## Parameters


`family: str`  

`y: list of float`  

`mu: list of float`  

`dispersion: float = ``1.0`  

`weights: list of float = None`  

`seed: int = ``0`  
Seeds the randomization.

`theta: float = None`  

`power: float = None`  


## Returns


`list of float`