Compute posterior draws of the linear predictor, that is draws before applying any link functions or other transformations. Can be performed for the data used to fit the model (posterior predictive checks) or for new data.

# S3 method for brmsfit
posterior_linpred(
object,
transform = FALSE,
newdata = NULL,
re_formula = NULL,
re.form = NULL,
resp = NULL,
dpar = NULL,
nlpar = NULL,
incl_thres = NULL,
ndraws = NULL,
draw_ids = NULL,
sort = FALSE,
...
)

## Arguments

object An object of class brmsfit. Logical; if FALSE (the default), draws of the linear predictor are returned. If TRUE, draws of transformed linear predictor, that is, after applying the link function are returned. 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. 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. Alias of re_formula. Optional names of response variables. If specified, predictions are performed only for the specified response variables. Name of a predicted distributional parameter for which draws are to be returned. By default, draws of the main distributional parameter(s) "mu" are returned. Optional name of a predicted non-linear parameter. If specified, expected predictions of this parameters are returned. Logical; only relevant for ordinal models when transform is FALSE, and ignored otherwise. Shall the thresholds and category-specific effects be included in the linear predictor? For backwards compatibility, the default is to not include them. 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. An integer vector specifying the posterior draws to be used. If NULL (the default), all draws are used. Logical. Only relevant for time series models. Indicating whether to return predicted values in the original order (FALSE; default) or in the order of the time series (TRUE). Further arguments passed to prepare_predictions that control several aspects of data validation and prediction.

posterior_epred.brmsfit

## Examples

if (FALSE) {
## fit a model
fit <- brm(rating ~ treat + period + carry + (1|subject),
data = inhaler)

## extract linear predictor values
pl <- posterior_linpred(fit)
str(pl)
}