residuals.brmsfit {brms}  R Documentation 
This method is an alias of predictive_error.brmsfit
with additional arguments for obtaining summaries of the computed samples.
## S3 method for class 'brmsfit' residuals( object, newdata = NULL, re_formula = NULL, method = "pp_expect", type = c("ordinary", "pearson"), resp = NULL, nsamples = NULL, subset = NULL, sort = FALSE, summary = TRUE, robust = FALSE, probs = c(0.025, 0.975), ... )
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 
method 
Method use to obtain predictions. Either

type 
The type of the residuals,
either 
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 ( 
summary 
Should summary statistics be returned
instead of the raw values? Default is 
robust 
If 
probs 
The percentiles to be computed by the 
... 
Further arguments passed to 
Residuals of type 'ordinary'
are of the form R = Y 
Yrep, where Y is the observed and Yrep is the predicted response.
Residuals of type pearson
are of the form R = (Y  Yrep) /
SD(Y), where SD(Y) is an estimation of the standard deviation of
Y.
An array
of predictive error/residual samples. If
summary = FALSE
the output resembles those of
predictive_error.brmsfit
. If summary = TRUE
the output
is an N x E matrix, where N is the number of observations and E denotes
the summary statistics computed from the samples.
## Not run: ## fit a model fit < brm(rating ~ treat + period + carry + (1subject), data = inhaler, cores = 2) ## extract residuals/predictive errors res < residuals(fit) head(res) ## End(Not run)