sar: Spatial simultaneous autoregressive (SAR) structures

In brms: Bayesian Regression Models using 'Stan'

Spatial simultaneous autoregressive (SAR) structures

Description

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.

Usage

sar(M, type = "lag")

Arguments

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.

Details

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.

Value

An object of class 'sar_term', which is a list of arguments to be interpreted by the formula parsing functions of brms.

See Also

autocor-terms

Examples

## Not run: 
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)

## End(Not run)

brms documentation built on Sept. 23, 2024, 5:08 p.m.