predictive_error.brmsfit {brms}  R Documentation 
Compute posterior samples of predictive errors, that is, observed minus predicted responses. Can be performed for the data used to fit the model (posterior predictive checks) or for new data.
## S3 method for class 'brmsfit' predictive_error( object, newdata = NULL, re_formula = NULL, re.form = NULL, resp = NULL, nsamples = NULL, subset = NULL, sort = FALSE, ... )
object 
An object of class 
newdata 
An optional data.frame for which to evaluate predictions. If

re_formula 
formula containing grouplevel effects to be considered in
the prediction. If 
re.form 
Alias of 
resp 
Optional names of response variables. If specified, predictions are performed only for the specified response variables. 
nsamples 
Positive integer indicating how many posterior samples should
be used. If 
subset 
A numeric vector specifying the posterior samples to be used.
If 
sort 
Logical. Only relevant for time series models.
Indicating whether to return predicted values in the original
order ( 
... 
Further arguments passed to 
An S x N array
of predictive error samples, where S is the
number of posterior samples and N is the number of observations.
## Not run: ## fit a model fit < brm(rating ~ treat + period + carry + (1subject), data = inhaler, cores = 2) ## extract predictive errors pe < predictive_error(fit) str(pe) ## End(Not run)