Creates \(n \times n\) matrix indicating the difference in times of adoption between each pair of nodes
toa_diff(obj, t0 = NULL, labels = NULL)
| obj | Either an integer vector of size \(n\) containing time of adoption of the innovation,
or a |
|---|---|
| t0 | Integer scalar. Sets the lower bound of the time window (e.g. 1955). |
| labels | Character vector of size \(n\). Labels (ids) of the vertices. |
An \(n \times n\) symmetric matrix indicating the difference in times of adoption between each pair of nodes.
Each cell ij of the resulting matrix is calculated as \(toa_j - toa_i\), so that whenever its positive it means that the j-th individual (alter) adopted the innovation sooner.
# Generating a random vector of time set.seed(123) times <- sample(2000:2005, 10, TRUE) # Computing the TOA differences toa_diff(times)#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] #> [1,] 0 3 0 -1 -1 3 0 2 1 3 #> [2,] -3 0 -3 -4 -4 0 -3 -1 -2 0 #> [3,] 0 3 0 -1 -1 3 0 2 1 3 #> [4,] 1 4 1 0 0 4 1 3 2 4 #> [5,] 1 4 1 0 0 4 1 3 2 4 #> [6,] -3 0 -3 -4 -4 0 -3 -1 -2 0 #> [7,] 0 3 0 -1 -1 3 0 2 1 3 #> [8,] -2 1 -2 -3 -3 1 -2 0 -1 1 #> [9,] -1 2 -1 -2 -2 2 -1 1 0 2 #> [10,] -3 0 -3 -4 -4 0 -3 -1 -2 0