Creates a square matrix suitable for spatial statistics models.

Description

Creates a square matrix suitable for spatial statistics models.

Usage

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diag_expand(...)

## S3 method for class 'list'
diag_expand(graph, self = getOption("diffnet.self"),
  valued = getOption("diffnet.valued"), ...)

## S3 method for class 'diffnet'
diag_expand(graph, self = getOption("diffnet.self"),
  valued = getOption("diffnet.valued"), ...)

## S3 method for class 'matrix'
diag_expand(graph, nper, self = getOption("diffnet.self"),
  valued = getOption("diffnet.valued"), ...)

## S3 method for class 'array'
diag_expand(graph, self = getOption("diffnet.self"),
  valued = getOption("diffnet.valued"), ...)

## S3 method for class 'dgCMatrix'
diag_expand(graph, nper, self = getOption("diffnet.self"),
  valued = getOption("diffnet.valued"), ...)

Arguments

...

Further arguments to be passed to the method.

graph

Any class of accepted graph format (see netdiffuseR-graphs).

self

Logical scalar. When TRUE allows loops (self edges).

valued

Logical scalar. When TRUE weights will be considered. Otherwise non-zero values will be replaced by ones.

nper

Integer scalar. Number of time periods of the graph.

Value

A square matrix of class dgCMatrix of size (nnode(g)*nper)^2

Examples

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# Simple example ------------------------------------------------------------
set.seed(23)
g <- rgraph_er(n=10, p=.5, t=2,undirected=TRUE)

# What we've done: A list with 2 bernoulli graphs
g

# Expanding to a 20*20 matrix with structural zeros on the diagonal
# and on cell 'off' adjacency matrix
diag_expand(g)

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