cor_car {brms}  R Documentation 
(Deprecated) Spatial conditional autoregressive (CAR) structures
Description
These function are deprecated. Please see car
for the new
syntax. These functions are constructors for the cor_car
class
implementing spatial conditional autoregressive structures.
Usage
cor_car(W, formula = ~1, type = "escar")
cor_icar(W, formula = ~1)
Arguments
W 
Adjacency matrix of locations.
All nonzero entries are treated as if the two locations
are adjacent. If 
formula 
An optional onesided formula of the form

type 
Type of the CAR structure. Currently implemented
are 
Details
The escar
and esicar
types are
implemented based on the case study of Max Joseph
(https://github.com/mbjoseph/CARstan). The icar
and
bym2
type is implemented based on the case study of Mitzi Morris
(https://mcstan.org/users/documentation/casestudies/icar_stan.html).
Examples
## Not run:
# generate some spatial data
east < north < 1:10
Grid < expand.grid(east, north)
K < nrow(Grid)
# set up distance and neighbourhood matrices
distance < as.matrix(dist(Grid))
W < array(0, c(K, K))
W[distance == 1] < 1
# generate the covariates and response data
x1 < rnorm(K)
x2 < rnorm(K)
theta < rnorm(K, sd = 0.05)
phi < rmulti_normal(
1, mu = rep(0, K), Sigma = 0.4 * exp(0.1 * distance)
)
eta < x1 + x2 + phi
prob < exp(eta) / (1 + exp(eta))
size < rep(50, K)
y < rbinom(n = K, size = size, prob = prob)
dat < data.frame(y, size, x1, x2)
# fit a CAR model
fit < brm(y  trials(size) ~ x1 + x2, data = dat,
family = binomial(), autocor = cor_car(W))
summary(fit)
## End(Not run)