excursions.variances: Calculate variances from a sparse precision matrix

In finnlindgren/excursions: Excursion Sets and Contour Credibility Regions for Random Fields

Description

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	Decides the number of threads the program can use. Set to 0 for using the maximum number of threads allowed by the system (default).

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.

Value

A vector with the variances.

Author(s)

David Bolin [e-mail]

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))

finnlindgren/excursions documentation built on Jan. 17, 2021, 12:20 a.m.