GibbsSteps_kcycle {systemicrisk}

Gibbs sampling step of a matrix in the ERE model

Description

The sampling is conditional on row and column sums and uses k-cycle steps. Then dimensions of L, lambda and p must match.

Usage

GibbsSteps_kcycle(L, lambda, p, it = 1000L, eps = 1e-10, debug = 0L)

Arguments

L

Starting matrix - will be modified to contain the results.

lambda

Matrix of intensities

p

Matrix of probabilities (must be in [0,1])

it

Number of iterations (default=1000)

eps

Threshold for values to be interpreted as equal to 0 (default = 1e-10)

debug

Should addtional debug information be printed? (0 no output, 1 output debug information)

Value

no return value

Examples

L <- matrix(c(1,2,3,4,5,6,7,8,9),nrow=3)
diag(L) <- 0
lambda <- matrix(0.5,nrow=3,ncol=3)
p <- matrix(0.7, nrow=3,ncol=3)
diag(p) <- 0
GibbsSteps_kcycle(L=L,lambda=lambda,p=p)
L
L <- matrix(1:16,nrow=4)
diag(L) <- 0
lambda <- matrix(0.5,nrow=4,ncol=4)
p <- matrix(0.25, nrow=4,ncol=4)
diag(p) <- 0
GibbsSteps_kcycle(L=L,lambda=lambda,p=p)
L