This function calculates the estimated standard deviations,
correlations and covariances of the group-level terms
in a multilevel model of class `brmsfit`

.
For linear models, the residual standard deviations,
correlations and covariances are also returned.

```
# S3 method for brmsfit
VarCorr(
x,
sigma = 1,
summary = TRUE,
robust = FALSE,
probs = c(0.025, 0.975),
...
)
```

## Arguments

- x
An object of class `brmsfit`

.

- sigma
Ignored (included for compatibility with
`VarCorr`

).

- 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`

.

- ...
Currently ignored.

## Value

A list of lists (one per grouping factor), each with
three elements: a matrix containing the standard deviations,
an array containing the correlation matrix, and an array
containing the covariance matrix with variances on the diagonal.

## Examples

```
if (FALSE) {
fit <- brm(count ~ zAge + zBase * Trt + (1+Trt|visit),
data = epilepsy, family = gaussian(), chains = 2)
VarCorr(fit)
}
```