chol {BNSP} | R Documentation |
The Cholesky and modified Cholesky decompositions
Description
Computes the Cholesky factorization and modified Cholesky factorizations of a real symmetric positive-definite square matrix.
Usage
chol(x, mod = TRUE, p = 1, ...)
Arguments
x |
A symmetric, positive-definite matrix. |
mod |
Defaults to TRUE. With this choice, the function returns the modified Cholesky decomposition. When mod = FALSE, the function returns the usual Cholesky decomposition. |
p |
Relevant only when |
... |
other arguments. |
Details
The function computes the modified Cholesky decomposition of a real symmetric positive-definite square matrix \Sigma
. This is given by
L \Sigma L^{\top} = D,
where L
is a lower tringular matrix with ones on its main diagonal and D is a block diagonal matrix with block size determined by argument p
.
Value
The function returns matrices L
and D
.
Author(s)
Georgios Papageorgiou gpapageo@gmail.com
See Also
The default function from base, chol
Examples
Sigma <- matrix(c(1.21,0.18,0.13,0.41,0.06,0.23,
0.18,0.64,0.10,-0.16,0.23,0.07,
0.13,0.10,0.36,-0.10,0.03,0.18,
0.41,-0.16,-0.10,1.05,-0.29,-0.08,
0.06,0.23,0.03,-0.29,1.71,-0.10,
0.23,0.07,0.18,-0.08,-0.10,0.36),6,6)
LD <- chol(Sigma)
L <- LD$L
D <- LD$D
round(L,5)
round(D,5)
solve(L) %*% D %*% solve(t(L))
LD <- chol(Sigma, p = 2)
L <- LD$L
D <- LD$D
round(L, 5)
round(D, 5)
solve(L) %*% D %*% solve(t(L))