# samplestats

##### Sampling Statistics

The function computes the average the log-likelihood, log-posterior, the deviance
information criterion and estimated degrees of freedom from samples of, e.g., a
`bamlss`

object.

- Keywords
- regression

##### Usage

```
samplestats(samples, x = NULL, y = NULL,
family = NULL, logLik = FALSE, ...)
```

##### Arguments

- samples
An object of class

`"mcmc.list"`

or`"bamlss"`

which contains MCMC samples.- x
The

`x`

list as returned by function`bamlss.frame`

.- y
The model response, as returned by function

`bamlss.frame`

- family
A

`bamlss.family`

object.- logLik
Logical, should the log-likelihood be computed, may take some time!

- …
Currently not used.

##### Details

If the log-likelihood is not available in the samples, the function tries to compute
the information. Depending on the complexity of the model, this may take some time.
Computations are based on the `$d()`

or `$loglik()`

function of the
`bamlss.family`

object.

If a `bamlss.family`

object contains a function `$p2d()`

or `$p2loglik()`

,
which computes the log-likelihood from parameters, these functions are used for computation.

##### Value

A list with the following entries (if available):

The average log-likelihood.

The average log-posterior.

The deviance information criterion.

The estimated degrees of freedom.

##### See Also

##### Examples

```
# NOT RUN {
## Generate some data.
d <- GAMart()
## Estimate model without sampling statistics
b <- bamlss(num ~ s(x1) + s(x2) + s(x3) + te(lon,lat),
data = d, samplestats = FALSE)
## Note: needs the $d() or $loglik() function in the family!
names(family(b))
## Compute sampling statistics.
samplestats(b)
# }
```

*Documentation reproduced from package bamlss, version 1.1-2, License: GPL-2 | GPL-3*