Constructs the intrinsic CAR precision matrix $$Q = \tau \, s (D - A),$$ where \(s\) is a scaling constant chosen so that the geometric mean of the marginal variances equals 1.
intrinsic_car_precision(
A,
tau = 1,
scale = TRUE,
symmetrize = FALSE,
check = TRUE
)A symmetric sparse precision matrix (`"dsCMatrix"`).
Square adjacency/weight matrix.
Positive scalar precision multiplier.
Logical; if `TRUE`, applies Besag scaling.
If `TRUE`, replaces `A` by `(A + t(A))/2`.
If `TRUE`, performs basic validation and warnings.
The resulting precision matrix is singular with rank deficiency equal to the number of connected components.
Sørbye, S. H. and Rue, H. (2014). Scaling intrinsic Gaussian Markov random field priors.