These functions take an lgpmodel object, and

`prior_pred`

samples from the prior predictive distribution of the model`sample_param_prior`

samples only its parameter prior using`sampling`

```
prior_pred(
model,
verbose = TRUE,
quiet = FALSE,
refresh = 0,
STREAM = get_stream(),
...
)
sample_param_prior(model, verbose = TRUE, quiet = FALSE, ...)
```

- model
An object of class lgpmodel.

- verbose
Should more information and a possible progress bar be printed?

- quiet
This forces

`verbose`

to be`FALSE`

. If you want to suppress also the output from Stan, give the additional argument`refresh=0`

.- refresh
Argument for

`sampling`

.- STREAM
External pointer. By default obtained with

`rstan::get_stream()`

.- ...
Additional arguments for

`sampling`

.

`prior_pred`

returns a list with components`y_draws`

: A matrix containing the prior predictive draws as rows. Can be passed to`bayesplot::pp_check()`

for graphical prior predictive checking.`pred_draws`

: an object of class Prediction, containing prior draws of each model component and their sum`param_draws`

: a`stanfit`

object of prior parameter draws (obtained by calling`sample_param_prior`

internally)

`sample_param_prior`

returns an object of class`stanfit`

Other main functions:
`create_model()`

,
`draw_pred()`

,
`get_draws()`

,
`lgp()`

,
`pred()`

,
`sample_model()`