Skip to contents

Combine multiple netify objects

Source: R/bind_netifies.R
bind_netifies.Rd

bind_netifies() concatenates two or more netify objects along the time axis (for combining cross-sec -> longit, or stacking two longit panels into a longer one). all inputs must share the same mode (unipartite / bipartite), symmetry, layers, and (for cross-sec inputs) the same actor set. actor sets across periods may differ – the result is a longit_list.

Usage

bind_netifies(
  ...,
  names = NULL,
  align_actors = c("none", "union", "intersection")
)

Arguments

...

two or more netify objects, or a single list of netify objects.

names

optional character vector to name the resulting periods. if NULL, periods are auto-named from the inputs' existing period labels (with deduplication if collisions).

align_actors

one of "none" (default), "union", or "intersection". controls how per-period actor sets are reconciled when inputs differ:

  • "none": keep each period's actor set as supplied; resulting longit_list periods may have different dimensions (matches prior behavior).

  • "union": take the union of actor sets across all inputs and pad each period with na rows/columns for actors not originally present.

  • "intersection": take the intersection of actor sets across all inputs and subset each period to only those actors.

Value

a longit_list netify object.

Details

for combining different layers of the same time slice, use layer_netify().

this is not the same as layer_netify():

  • bind_netifies() joins along time.

  • layer_netify() joins along relation (layer).

nodal and dyadic attributes are concatenated per-period; if two inputs supply conflicting values for the same (actor, time), the later input wins (with a one-shot inform).

when downstream models (e.g., tergm cmle) require uniform actor composition across periods, use align_actors = "union" or "intersection".

multilayer inputs are supported when each input has the same layer labels. the result is a longitudinal list whose per-period elements keep the layer dimension, so as.matrix(x, time = ..., layer = ...), unnetify(), and decompose_netify() can still address layers.

Author

cassy dorff, shahryar minhas

Examples

# \donttest{
data(icews)
n1 <- netify(icews[icews$year == 2010, ],
actor1 = "i", actor2 = "j", symmetric = FALSE,
weight = "verbCoop")
n2 <- netify(icews[icews$year == 2011, ],
actor1 = "i", actor2 = "j", symmetric = FALSE,
weight = "verbCoop")
combined <- bind_netifies(n1, n2, names = c("2010", "2011"))
summary(combined)
#>    net num_actors   density num_edges prop_edges_missing mean_edge_weight
#> 1 2010        152 0.4346462      9976                  0         41.72113
#> 2 2011        152 0.4229697      9708                  0         37.33642
#>   sd_edge_weight median_edge_weight min_edge_weight max_edge_weight
#> 1       198.3157                  6               1            4937
#> 2       172.2944                  5               1            5581
#>   competition_row competition_col sd_of_row_means sd_of_col_means
#> 1      0.04071163      0.03493156         41.4412        37.76971
#> 2      0.03964994      0.03405077         35.5239        32.37731
#>   covar_of_row_col_means reciprocity    mutual transitivity
#> 1              0.9934913   0.9823385 0.8402509    0.6386063
#> 2              0.9903188   0.9763723 0.8327355    0.6220630
# }