This method helps in preparing brms models for certin post-processing
tasks most notably various forms of predictions. Unless you are a package
developer, you will rarely need to call `prepare_predictions`

directly.

```
# S3 method for brmsfit
prepare_predictions(
x,
newdata = NULL,
re_formula = NULL,
allow_new_levels = FALSE,
sample_new_levels = "uncertainty",
incl_autocor = TRUE,
oos = NULL,
resp = NULL,
ndraws = NULL,
draw_ids = NULL,
nsamples = NULL,
subset = NULL,
nug = NULL,
smooths_only = FALSE,
offset = TRUE,
newdata2 = NULL,
new_objects = NULL,
point_estimate = NULL,
ndraws_point_estimate = 1,
...
)
prepare_predictions(x, ...)
```

- x
An R object typically of class

`'brmsfit'`

.- newdata
An optional data.frame for which to evaluate predictions. If

`NULL`

(default), the original data of the model is used.`NA`

values within factors are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.- re_formula
formula containing group-level effects to be considered in the prediction. If

`NULL`

(default), include all group-level effects; if`NA`

, include no group-level effects.- allow_new_levels
A flag indicating if new levels of group-level effects are allowed (defaults to

`FALSE`

). Only relevant if`newdata`

is provided.- sample_new_levels
Indicates how to sample new levels for grouping factors specified in

`re_formula`

. This argument is only relevant if`newdata`

is provided and`allow_new_levels`

is set to`TRUE`

. If`"uncertainty"`

(default), each posterior sample for a new level is drawn from the posterior draws of a randomly chosen existing level. Each posterior sample for a new level may be drawn from a different existing level such that the resulting set of new posterior draws represents the variation across existing levels. If`"gaussian"`

, sample new levels from the (multivariate) normal distribution implied by the group-level standard deviations and correlations. This options may be useful for conducting Bayesian power analysis or predicting new levels in situations where relatively few levels where observed in the old_data. If`"old_levels"`

, directly sample new levels from the existing levels, where a new level is assigned all of the posterior draws of the same (randomly chosen) existing level.- incl_autocor
A flag indicating if correlation structures originally specified via

`autocor`

should be included in the predictions. Defaults to`TRUE`

.- oos
Optional indices of observations for which to compute out-of-sample rather than in-sample predictions. Only required in models that make use of response values to make predictions, that is, currently only ARMA models.

- resp
Optional names of response variables. If specified, predictions are performed only for the specified response variables.

- ndraws
Positive integer indicating how many posterior draws should be used. If

`NULL`

(the default) all draws are used. Ignored if`draw_ids`

is not`NULL`

.- draw_ids
An integer vector specifying the posterior draws to be used. If

`NULL`

(the default), all draws are used.- nsamples
Deprecated alias of

`ndraws`

.- subset
Deprecated alias of

`draw_ids`

.- nug
Small positive number for Gaussian process terms only. For numerical reasons, the covariance matrix of a Gaussian process might not be positive definite. Adding a very small number to the matrix's diagonal often solves this problem. If

`NULL`

(the default),`nug`

is chosen internally.- smooths_only
Logical; If

`TRUE`

only predictions related to the- offset
Logical; Indicates if offsets should be included in the predictions. Defaults to

`TRUE`

.- newdata2
A named

`list`

of objects containing new data, which cannot be passed via argument`newdata`

. Required for some objects used in autocorrelation structures, or`stanvars`

.- new_objects
Deprecated alias of

`newdata2`

.- point_estimate
Shall the returned object contain only point estimates of the parameters instead of their posterior draws? Defaults to

`NULL`

in which case no point estimate is computed. Alternatively, may be set to`"mean"`

or`"median"`

. This argument is primarily implemented to ensure compatibility with the`loo_subsample`

method.- ndraws_point_estimate
Only used if

`point_estimate`

is not`NULL`

. How often shall the point estimate's value be repeated? Defaults to`1`

.- ...
Further arguments passed to

`validate_newdata`

.

An object of class `'brmsprep'`

or `'mvbrmsprep'`

,
depending on whether a univariate or multivariate model is passed.