Calculate variances from a sparse precision matrix

excursions.variances calculates the diagonal of the inverse of a sparse symmetric positive definite matrix Q.

Usage

excursions.variances(L, Q, max.threads = 0)

Arguments

L

Cholesky factor of precision matrix.

Q

Precision matrix.

max.threads

The number of threads that the program can use. The default, 0, uses the default number of threads of OpenMP, which can be set with the environment variable OMP_NUM_THREADS. The number of threads is at most OMP_THREAD_LIMIT, and is one if the package was built without OpenMP. The results do not depend on the number of threads.

Value

A vector with the variances.

Details

The method for calculating the diagonal requires the Cholesky factor, L, of Q, which should be supplied if available. If Q is provided, the cholesky factor is calculated and the variances are then returned in the same ordering as Q. If L is provided, the variances are returned in the same ordering as L, even if L@invpivot exists.

Author

David Bolin davidbolin@gmail.com

Examples

## Create a tridiagonal precision matrix
n <- 21
Q <- Matrix(toeplitz(c(1, -0.1, rep(0, n - 2))))
v2 <- excursions.variances(Q = Q, max.threads = 2)
## var2 should be the same as:
v1 <- diag(solve(Q))