residuals.brmsfit.Rmd

---
title: "``brms::residuals.brmsfit``"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(brms)
```

#### Description 
Extract Model Residuals from brmsfit Objects

#### Usage
<pre><code>
## S3 method for class '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), ...)
</code></pre>
<pre><code>
## S3 method for class '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), ...)
</code></pre>
#### 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.
* ``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.
* type The type of the residuals, either "ordinary" or "pearson". More information
is provided under ’Details’.
* method Indicates the method to compute model impliedvalues. Either "fitted" (predicted values of the regression curve) or "predict" (predicted responsevalues).
Using "predict" is recommended but "fitted" is the current default for reasons of backwards compatibility.
* `` 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 NULL (the default) all samples are used. Ignored if subset is not NULL.
* ``subset``: A numeric vector specifying the posterior samples to be used. If NULL (the default), all samples are used.
* ``sort``: Logical. Only relevant for time series models. Indicating whether to return predictedvalues in the original order (FALSE; default) or in the order of the time
series (TRUE).
* ``summary``: Should summary statistics (i.e. means, sds, and 95% intervals) be returned instead
of the rawvalues? 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 extract_draws that control several aspects of data validation and prediction.
* ``re.form``: Alias of ``re_formula``.


#### Examples

```{r}

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

```{r}
## extract residuals
res <- residuals(fit, summary = TRUE)
head(res)

```
#### Details
Residuals of type ordinary are of the form R = Y 􀀀 Y p, where Y is the observed and Y p is the
predicted response. Residuals of type pearson are of the form R = (Y 􀀀 Y p)=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.

#### 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.
restructure 141