# Evaluate or sample from a posterior result given a model and locations

Source:`R/model.R`

`evaluate_model.Rd`

Evaluate or sample from a posterior result given a model and locations

## Usage

```
evaluate_model(
model,
state,
data = NULL,
input = NULL,
comp_simple = NULL,
predictor = NULL,
format = NULL,
used = NULL,
...
)
evaluate_state(
model,
result,
property = "mode",
n = 1,
seed = 0L,
num.threads = NULL,
internal_hyperpar = FALSE,
...
)
```

## Arguments

- model
A bru model

- state
list of state lists, as generated by

`evaluate_state()`

- data
A

`list`

,`data.frame`

, or`Spatial*DataFrame`

, with coordinates and covariates needed to evaluate the predictor.- input
Precomputed inputs list for the components

- comp_simple
Precomputed

`comp_simple_list`

for the components- predictor
A formula or an expression to be evaluated given the posterior or for each sample thereof. The default (

`NULL`

) returns a`data.frame`

containing the sampled effects. In case of a formula the right hand side is used for evaluation.- format
character; determines the storage format of predictor output. Available options:

`"auto"`

If the first evaluated result is a vector or single-column matrix, the "matrix" format is used, otherwise "list".`"matrix"`

A matrix where each column contains the evaluated predictor expression for a state.`"list"`

A list where each element contains the evaluated predictor expression for a state.

- used
A

`bru_used()`

object, or NULL (default)- ...
Additional arguments passed on to

`inla.posterior.sample`

- result
- property
Property of the model components to obtain value from. Default: "mode". Other options are "mean", "0.025quant", "0.975quant", "sd" and "sample". In case of "sample" you will obtain samples from the posterior (see

`n`

parameter). If`result`

is`NULL`

, all-zero vectors are returned for each component.- n
Number of samples to draw.

- seed
If seed != 0L, the random seed

- num.threads
Specification of desired number of threads for parallel computations. Default NULL, leaves it up to INLA. When seed != 0, overridden to "1:1"

- internal_hyperpar
logical; If

`TRUE`

, return hyperparameter properties on the internal scale. Currently ignored when`property="sample"`

. Default is`FALSE`

.