diag_expand: Creates a square matrix suitable for spatial statistics...

In netdiffuseR: Analysis of Diffusion and Contagion Processes on Networks

Creates a square matrix suitable for spatial statistics models.

Description

Creates a square matrix suitable for spatial statistics models.

Usage

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.

Value

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)

netdiffuseR documentation built on Aug. 30, 2023, 5:07 p.m.