residuals.brmsfit {brms}  R Documentation 
Posterior Draws of Residuals/Predictive Errors
Description
This method is an alias of predictive_error.brmsfit
with additional arguments for obtaining summaries of the computed draws.
Usage
## S3 method for class 'brmsfit'
residuals(
object,
newdata = NULL,
re_formula = NULL,
method = "posterior_predict",
type = c("ordinary", "pearson"),
resp = NULL,
ndraws = NULL,
draw_ids = NULL,
sort = FALSE,
summary = TRUE,
robust = FALSE,
probs = c(0.025, 0.975),
...
)
Arguments
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 used to obtain predictions. Can be set to

type 
The type of the residuals,
either 
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 
draw_ids 
An integer vector specifying the posterior draws 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 
Details
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(Yrep)
, where SD(Yrep)
is an estimate of the standard deviation of
Yrep
.
Value
An array
of predictive error/residual draws. 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 draws.
Examples
## 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)