These functions describe the missingness in network data:
net_node_missing() returns the proportion of nodes that are missing in a network.
net_node_incomplete() returns the proportion of the network's node
attribute values that are unknown.
net_tie_missing() returns the proportion of ties that are missing in a network.
net_tie_incomplete() returns the proportion of the network's ties whose
value is unknown.
A network is missing a tie where the tie itself was not observed,
so that whether it exists is not known.
A tie or a node is incomplete where it is there and observed,
but an attribute of it is not known.
A weight of NA therefore marks an incomplete tie and not a missing one.
impute_ties() and impute_nodes() impute each of these states.
A tie recorded as missing is one that could have been observed and was not.
It is not a tie, so net_ties() does not count it,
and it is not the absence of a tie either.
See as_missinglist() for how each class records them,
and make_stocnet() for how they differ from a node's absence
and from a tie of unknown value.
For a multiplex or longitudinal network, net_tie_missing() counts the ties
that could have been observed over each layer and each moment the network
records. Coercing such a network to a matrix first gives a higher
proportion, since a matrix holds only one cell for each dyad.
net_node_missing(.data)
net_tie_missing(.data)
net_node_incomplete(.data)
net_tie_incomplete(.data)An object of a {manynet}-consistent class:
adjacency or incidence matrix from {base} R
edgelist data.frame from {base} R or tbl/tbl_df from {tibble}
stocnet stocnet, from the {manynet} package
igraph igraph, from the {igraph} package
network network, from the {network} package
tidygraph tbl_graph, from the {tidygraph} package
net_node_missing(), net_tie_missing(), net_node_incomplete(),
and net_tie_incomplete() return a scalar.
net_node_incomplete(fict_lotr)
#> [1] 0
net_tie_incomplete(ison_adolescents)
#> [1] 0