Extract Model Residuals from brmsfit Objects
# S3 method for brmsfit
residuals(object, newdata = NULL, re_formula = NULL,
type = c("ordinary", "pearson"), method = c("fitted", "predict"),
resp = NULL, nsamples = NULL, subset = NULL, sort = FALSE,
summary = TRUE, robust = FALSE, probs = c(0.025, 0.975), ...)# S3 method for brmsfit
predictive_error(object, newdata = NULL,
re_formula = NULL, re.form = NULL, resp = NULL, nsamples = NULL,
subset = NULL, sort = FALSE, robust = FALSE, probs = c(0.025,
0.975), ...)
An object of class brmsfit
.
An optional data.frame for which to evaluate predictions. If
NULL
(default), the original data of the model is used.
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.
The type of the residuals,
either "ordinary"
or "pearson"
.
More information is provided under 'Details'.
Indicates the method to compute
model implied values. Either "fitted"
(predicted values of the regression curve) or
"predict"
(predicted response values).
Using "predict"
is recommended
but "fitted"
is the current default for
reasons of backwards compatibility.
Optional names of response variables. If specified, predictions are performed only for the specified response variables.
Positive integer indicating how many posterior samples should
be used. If NULL
(the default) all samples are used. Ignored if
subset
is not NULL
.
A numeric vector specifying the posterior samples to be used.
If NULL
(the default), all samples 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
).
Should summary statistics
(i.e. means, sds, and 95% intervals) be returned
instead of the raw values? Default is TRUE
.
If FALSE
(the default) the mean is used as
the measure of central tendency and the standard deviation as
the measure of variability. If TRUE
, the median and the
median absolute deviation (MAD) are applied instead.
Only used if summary
is TRUE
.
The percentiles to be computed by the quantile
function. Only used if summary
is TRUE
.
Further arguments passed to extract_draws
that control several aspects of data validation and prediction.
Alias of re_formula
.
Model residuals. If summary = TRUE
this is a N x C matrix and if summary = FALSE
a S x N matrix, where S is the number of samples,
N is the number of observations, and C is equal to
length(probs) + 2
.
Residuals of type ordinary
are of the form \(R = Y - Yp\), where \(Y\) is the observed
and \(Yp\) is the predicted response.
Residuals of type pearson
are
of the form \(R = (Y - Yp) / SD(Y)\),
where \(SD(Y)\) is an estimation of the standard deviation
of \(Y\).
Currently, residuals.brmsfit
does not support
categorical
or ordinal models.
Method predictive_error.brmsfit
is an alias of
residuals.brmsfit
with method = "predict"
and
summary = FALSE
.
# NOT RUN {
## fit a model
fit <- brm(rating ~ treat + period + carry + (1|subject),
data = inhaler, cores = 2)
## extract residuals
res <- residuals(fit, summary = TRUE)
head(res)
# }
# NOT RUN {
# }
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