adopt_changes is just an
alias for select_egoalter.
select_egoalter(graph, adopt, period = NULL)
adopt_changes(graph, adopt, period = NULL)netdiffuseR-graphs).toa_mat.timeidselect_a_01, ..., select_a_16select_d_01, ..., select_d_16select_s_01, ..., select_s_16| Alter | |||||
| $t-1$ | No | ||||
| Yes | $t-1$ | $t$ | No | ||
| Yes | No | Yes | Ego | No | No |
| 1 | 2 | 9 | 10 | ||
| Yes | 3 | 4 | 11 | 12 | |
| Yes | No | 5 | 6 | 13 | 14 |
The first two Yes/No columns represent Ego's adoption of the innovation in $t-1$ and $t$; while the first two Yes/No rows represent Alter's adoption of the innovation in $t-1$ and t respectively. So for example, number 4 means that while neither of the two had addopted the innovation in $t-1$, both have in $t$. At the same time, number 12 means that ego adopted the innovation in $t$, but alter had already adopted in $t-1$ (so it has it in both, $t$ and $t-1$).
# Simple example
set.seed(1312)
dn <- rdiffnet(20, 5, seed.graph="small-world")
str(adopt_changes(dn))
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