Set up an spatial simultaneous autoregressive (SAR) term in brms. The function does not evaluate its arguments -- it exists purely to help set up a model with SAR terms.

`sar(M, type = "lag")`

- M
An object specifying the spatial weighting matrix. Can be either the spatial weight matrix itself or an object of class

`listw`

or`nb`

, from which the spatial weighting matrix can be computed.- type
Type of the SAR structure. Either

`"lag"`

(for SAR of the response values) or`"error"`

(for SAR of the residuals). More information is provided in the 'Details' section.

An object of class `'sar_term'`

, which is a list
of arguments to be interpreted by the formula
parsing functions of brms.

The `lagsar`

structure implements SAR of the response values:
$$y = \rho W y + \eta + e$$
The `errorsar`

structure implements SAR of the residuals:
$$y = \eta + u, u = \rho W u + e$$
In the above equations, \(\eta\) is the predictor term and \(e\) are
independent normally or t-distributed residuals. Currently, only families
`gaussian`

and `student`

support SAR structures.

```
if (FALSE) {
data(oldcol, package = "spdep")
fit1 <- brm(CRIME ~ INC + HOVAL + sar(COL.nb, type = "lag"),
data = COL.OLD, data2 = list(COL.nb = COL.nb),
chains = 2, cores = 2)
summary(fit1)
plot(fit1)
fit2 <- brm(CRIME ~ INC + HOVAL + sar(COL.nb, type = "error"),
data = COL.OLD, data2 = list(COL.nb = COL.nb),
chains = 2, cores = 2)
summary(fit2)
plot(fit2)
}
```