graph.matrix: Construct a neighbour-matrix from a 'graph'

In andrewzm/INLA: Functions which allow to perform full Bayesian analysis of latent Gaussian models using Integrated Nested Laplace Approximaxion

Description

Construct a neighbour-matrix from a graph and disaply it

Usage

    inla.graph2matrix(graph, ...)
    inla.spy(graph, ..., reordering = NULL, factor = 1.0, max.dim = NULL)

Arguments

graph	An inla.graph-object, a (sparse) symmetric matrix, a filename containing the graph, or a list or collection of characters and/or numbers defining the graph.
reordering	A possible reordering. Typical the one obtained from a inla-call, result$misc$reordering, or the result of inla.qreordering.
factor	A scaling of the inla.graph-object to reduce the size.
max.dim	Maximum dimension of the inla.graph-object plotted; if missing(factor) and max.dim is set, then factor is computed automatically to give the given max.dim.
...	Additional arguments to inla.read.graph()

Value

inla.graph2matrix returns a sparse symmetric matrix where the non-zero pattern is defined by the graph. The inla.spy function, plots a binary image of a graph. The reordering argument is typically the reordering used by inla, found in result$misc$reordering.

Author(s)

Havard Rue [e-mail]

See Also

inla.read.graph, inla.qreordering

Examples

n = 50
Q = matrix(0, n, n)
idx = sample(1:n, 2*n, replace=TRUE)
Q[idx, idx] = 1
diag(Q) = 1
g = inla.read.graph(Q)
QQ = inla.graph2matrix(g)
inla.spy(QQ)
print(all.equal(as.matrix(Q), as.matrix(QQ)))

g.file = inla.write.graph(g)
inla.dev.new()
inla.spy(g.file)
inla.spy(g.file,  reordering = inla.qreordering(g))

g = inla.read.graph(g.file)
inla.dev.new()
inla.spy(g)

inla.dev.new()
inla.spy(3, 1, "1 2 2 1 1 3 0")
inla.dev.new()
inla.spy(3, 1, "1 2 2 1 1 3 0", reordering = 3:1)

andrewzm/INLA documentation built on May 10, 2019, 11:12 a.m.