| car_precision | R Documentation | 
A convenience function to compute the CAR precision matrix based on a given adjacency matrix.
car_precision(A, tau = 1, scale = FALSE)
| A | An adjacency matrix. | 
| tau | The CAR dependency parameter  | 
| scale | Whether to scale matrix entries. See "Value".
Default:  | 
Suppose \bm{A} is an n \times n adjacency matrix and
  \bm{D} = \textrm{Diag}(\bm{A} \bm{1})
  = \textrm{Diag}(a_{1+}, \ldots, a_{n+}).
If scale is FALSE, return the CAR precision matrix
  \bm{Q} = \bm{D} - \tau \bm{A}.
If scale is TRUE, return a scaled version
  \tilde{\bm{Q}} = \bm{D}^{-1} \bm{Q}.
An error is thrown if scale = TRUE and any of
\{ a_{1+}, \ldots, a_{n+} \} are equal to 0.
Taking \tau = 1 corresponds to the Intrinsic CAR
precision matrix.
Typically in a modeling context, the precision matrix will be
multiplied by a scaling parameter; e.g., a CAR model for
random effects \bm{\phi} could be
  f(\bm{\phi} \mid \alpha) \propto
  \alpha^{-q} \exp\left\{ -\frac{1}{2 \alpha^2}
  \bm{\phi}^\top \bm{Q} \bm{\phi} \right\}.
where q = \textrm{rank}(Q).
CAR precision matrix.
data("acs_sf")
dom = acs5_2013[1:4,]
A = adjacency_matrix(dom)
Q = car_precision(A)
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