brms (version 0.9.1)

residuals.brmsfit: Extract Model Residuals from brmsfit Objects

Description

Extract Model Residuals from brmsfit Objects

Usage

## S3 method for class 'brmsfit':
residuals(object, newdata = NULL, re_formula = NULL,
  type = c("ordinary", "pearson"), allow_new_levels = FALSE,
  subset = NULL, nsamples = NULL, summary = TRUE, probs = c(0.025,
  0.975), ...)

Arguments

object

An object of class brmsfit

newdata

An optional data.frame for which to evaluate predictions. If NULL (default), the orginal data of the model is used.

re_formula

formula containing random effects to be considered in the prediction. If NULL (default), include all random effects; if NA, include no random effects.

type

The type of the residuals, either "ordinary" or "pearson". More information is provided under 'Details'.

allow_new_levels

A flag indicating if new levels of random effects are allowed (defaults to FALSE). Only relevant if newdata is provided.

subset

A numeric vector specifying the posterior samples to be used. If NULL (the default), all samples are used.

nsamples

Positive integer indicating how many posterior samples should be used. If NULL (the default) all samples are used. Ignored if subset is not NULL.

summary

Should summary statistics (i.e. means, sds, and 95% intervals) be returned instead of the raw values? Default is TRUE.

probs

The percentiles to be computed by the quantile function. Only used if summary is TRUE.

...

Currently ignored

Value

• 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.

Details

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.

Examples

## fit a model
fit <- brm(rating ~ treat + period + carry + (1|subject), 
           data = inhaler, cluster = 2)

## extract residuals 
res <- residuals(fit, summary = TRUE)
head(res)