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,
...
)
An object of class brmsfit
.
Logical; if FALSE
(the default), draws of the linear predictor are returned.
If TRUE
, draws of the transformed linear predictor,
that is, after applying the inverse 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.