## models.lppd()


In-sample log pointwise predictive density,


Usage


``` python
models.lppd(log_lik)
```


`sum_i log(mean_s p(y_i | theta_s))`.


## Parameters


`log_lik: list of list of float`  
One row per posterior draw, one column per observation.


## Returns


`float`  


## Examples

``` python
>>> import math
>>> from prospicio.models import lppd
>>> round(lppd([[math.log(0.5)], [math.log(0.25)]]), 12) == round(math.log(0.375), 12)
```

True