diag_expand function

Creates a square matrix suitable for spatial statistics models.

diag_expand(...)

## S3 method for class 'list'
diag_expand(graph, self = is_self(graph), valued = is_valued(graph), ...)

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

## S3 method for class 'matrix'
diag_expand(graph, nper, self = is_self(graph), valued = is_valued(graph), ...)

## S3 method for class 'array'
diag_expand(graph, self = is_self(graph), valued = is_valued(graph), ...)

## S3 method for class 'dgCMatrix'
diag_expand(graph, nper, self = is_self(graph), valued = is_valued(graph), ...)

Arguments

• ...: Further arguments to be passed to the method.
• graph: Any class of accepted graph format (see netdiffuseR-graphs).
• self: Logical scalar. When TRUE autolinks (loops, self edges) are allowed (see details).
• 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.

Returns

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

Examples

# 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)