Creates a square matrix suitable for spatial statistics models.

Creates a square matrix suitable for spatial statistics models.

diag_expand(...)

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

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

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

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

# S3 method for 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 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
#> $`1`
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>    [[ suppressing 10 column names ‘1’, ‘2’, ‘3’ ... ]]
#>                       
#> 1  . 1 . 1 1 1 . . . .
#> 2  1 . . 1 1 1 1 . 1 1
#> 3  . . . . 1 . 1 1 1 1
#> 4  1 1 . . 1 . 1 . . .
#> 5  1 1 1 1 . 1 1 1 . 1
#> 6  1 1 . . 1 . 1 1 . .
#> 7  . 1 1 1 1 1 . 1 . .
#> 8  . . 1 . 1 1 1 . 1 1
#> 9  . 1 1 . . . . 1 . 1
#> 10 . 1 1 . 1 . . 1 1 .
#> 
#> $`2`
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>    [[ suppressing 10 column names ‘1’, ‘2’, ‘3’ ... ]]
#>                       
#> 1  . 1 . . 1 . . . 1 .
#> 2  1 . . 1 . . . 1 . 1
#> 3  . . . . 1 1 1 . . 1
#> 4  . 1 . . 1 1 . 1 1 1
#> 5  1 . 1 1 . 1 . 1 . .
#> 6  . . 1 1 1 . . 1 1 .
#> 7  . . 1 . . . . 1 1 1
#> 8  . 1 . 1 1 1 1 . 1 .
#> 9  1 . . 1 . 1 1 1 . .
#> 10 . 1 1 1 . . 1 . . .
#> 
#> attr(,"undirected")
#> [1] TRUE

# Expanding to a 20*20 matrix with structural zeros on the diagonal
# and on cell 'off' adjacency matrix
diag_expand(g)
#> 20 x 20 sparse Matrix of class "dgCMatrix"
#>                                              
#>  [1,] . 1 . 1 1 1 . . . . . . . . . . . . . .
#>  [2,] 1 . . 1 1 1 1 . 1 1 . . . . . . . . . .
#>  [3,] . . . . 1 . 1 1 1 1 . . . . . . . . . .
#>  [4,] 1 1 . . 1 . 1 . . . . . . . . . . . . .
#>  [5,] 1 1 1 1 . 1 1 1 . 1 . . . . . . . . . .
#>  [6,] 1 1 . . 1 . 1 1 . . . . . . . . . . . .
#>  [7,] . 1 1 1 1 1 . 1 . . . . . . . . . . . .
#>  [8,] . . 1 . 1 1 1 . 1 1 . . . . . . . . . .
#>  [9,] . 1 1 . . . . 1 . 1 . . . . . . . . . .
#> [10,] . 1 1 . 1 . . 1 1 . . . . . . . . . . .
#> [11,] . . . . . . . . . . . 1 . . 1 . . . 1 .
#> [12,] . . . . . . . . . . 1 . . 1 . . . 1 . 1
#> [13,] . . . . . . . . . . . . . . 1 1 1 . . 1
#> [14,] . . . . . . . . . . . 1 . . 1 1 . 1 1 1
#> [15,] . . . . . . . . . . 1 . 1 1 . 1 . 1 . .
#> [16,] . . . . . . . . . . . . 1 1 1 . . 1 1 .
#> [17,] . . . . . . . . . . . . 1 . . . . 1 1 1
#> [18,] . . . . . . . . . . . 1 . 1 1 1 1 . 1 .
#> [19,] . . . . . . . . . . 1 . . 1 . 1 1 1 . .
#> [20,] . . . . . . . . . . . 1 1 1 . . 1 . . .