R: Posterior Draws of Residuals/Predictive Errors

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_epred",
      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 `brmsfit`.
`newdata` | An optional data.frame for which to evaluate predictions. If `NULL` (default), the original data of the model is used. `NA` values within factors are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.
`re_formula` | 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.
`method` | Method use to obtain predictions. Either `"posterior_epred"` (the default) or `"posterior_predict"`. Using `"posterior_predict"` is recommended but `"posterior_epred"` is the current default for reasons of backwards compatibility.
`type` | The type of the residuals, either `"ordinary"` or `"pearson"`. More information is provided under 'Details'.
`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 `NULL` (the default) all draws are used. Ignored if `draw_ids` is not `NULL`.
`draw_ids` | An integer vector specifying the posterior draws to be used. If `NULL` (the default), all draws are used.
`sort` | 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`).
`summary` | Should summary statistics be returned instead of the raw values? Default is `TRUE`..
`robust` | 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`.
`probs` | The percentiles to be computed by the `quantile` function. Only used if `summary` is `TRUE`.
`...` | Further arguments passed to `prepare_predictions` that control several aspects of data validation and prediction.

### 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 + (1|subject),
               data = inhaler, cores = 2)

    ## extract residuals/predictive errors
    res <- residuals(fit)
    head(res)

    ## End(Not run)

[Package brms version 2.16.3 Index]