## distributions.claim_count()


The claim count with this mean and dispersion `Var[N] / E[N]`:


Usage


``` python
distributions.claim_count(
    mean,
    dispersion,
)
```


binomial below 1, Poisson at 1, negative binomial above 1.

A binomial needs a whole number of trials, so below 1 the trials are `mean / (1 - dispersion)` rounded up: the mean is kept and the dispersion moves up to the nearest attainable value.


## Parameters


`mean: float`  

`dispersion: float`  
Positive.


## Returns


`Binomial or Poisson or NegativeBinomial`  


## Examples

``` python
>>> from prospicio.distributions import claim_count
>>> claim_count(4.0, 2.5)
```

NegativeBinomial(r=2.6666666666666665, beta=1.5)