## risk.mean_excess()


The empirical mean-excess function `e(u) = E[X - u | X > u]` at each


Usage


``` python
risk.mean_excess(
    draws,
    thresholds,
)
```


threshold, linear above a threshold where a GPD fits.


## Parameters


`draws: list of float`  

`thresholds: list of float`  


## Returns


`list of (float, float, int)`  
`(u, e(u), number of draws above u)`; `e(u)` is NaN when none are.


## Examples

``` python
>>> from prospicio.risk import mean_excess
>>> mean_excess([1.0, 2.0, 3.0, 4.0], [2.0])
```

\[(2.0, 1.5, 2)\]