`nwkplex`

Maximal k-plex enumeration

Syntax

nwkplex
[netlist]
[,
k(int)
generate(newvarname)
replace
minsize(int)
silent]


`k(int)`	How many ties each member may miss; default = 2
`generate(newvarname)`	Name of the Stata variable that stores each node’s largest maximal-k-plex membership size; default = _kplexnum
`replace`	Replace existing variable
`minsize(int)`	Smallest k-plex size to report; default = k+1
`silent`	Suppress display of results

Description

nwkplex enumerates every maximal k-plex in the network(s) in netlist - a “relaxed clique”: a set of nodes in which every member is tied to all but at most k(int) - 1 of the other members (a plain clique is the special case k=1, where nobody may miss any tie - nwclique already handles that case with a cheaper, purpose-built algorithm, so nwkplex requires k(int) >= 2). A k-plex is maximal if no further node could be added to it without breaking that property. Enumeration uses the same Bron and Kerbosch (1973)-style recursive backtracking nwclique uses, generalized to the k-plex membership rule (Seidman and Foster 1978).

Like cliques, k-plexes genuinely overlap - a node can belong to several at once - so there is no single per-node k-plex-membership variable the way there is a single component or community id. nwkplex generates a variable holding, for each node, the size of the largest maximal k-plex it belongs to - a single, well-defined per-node summary - and returns the full k-plex list (as a k-plexes-by-nodes 0/1 membership matrix) in r(kplex_matrix) for anyone who needs the complete overlapping structure.

minsize(int) filters out k-plexes smaller than the given size before generating and returning results. This matters more for k-plexes than for cliques: by the formal definition above, any set of k(int) or fewer nodes is trivially a valid k-plex regardless of whether its members are tied at all (with k(int)=2, for example, any two nodes - tied or not - miss at most 1 of their 1 possible tie, satisfying the rule) - such tiny, structurally-uninteresting sets are usually not what “k-plex” is meant to capture. The default of k+1 is the smallest size at which the constraint can actually rule anything out, so it excludes every automatically-valid, uninformative case while still reporting the smallest genuinely constrained k-plexes. A node that belongs to no k-plex meeting minsize(int) gets a missing value in the generated variable, not a spurious 0.

Examples

. nwwebuse florentine, nwclear
. nwkplex flomarriage
. nwkplex flomarriage, k(3) replace

Supported network types

Binary: yes. Directed: yes, automatically symmetrized (a k-plex’s own definition - a bound on each member’s own missing-tie count - has no natural directed generalization, the same reasoning nwclique already applies). Weighted: not used - only presence/absence of a tie matters. Signed: not checked. Two-mode: not checked - operates on the network’s own square adjacency matrix. Maximal k-plex enumeration is worst-case exponential (a mathematical property of the problem itself, true of any correct algorithm) and, for a fixed network, generally slower than nwclique’s own clique enumeration for the same reason its own “Supported network types” section already notes for cliques, compounded further here since checking whether a candidate can still be added requires examining the whole candidate set’s own induced structure, not just a simple neighbor lookup - fine for the moderate network sizes typical of SNA datasets, not specially guarded against here beyond this note.

Stored results

Scalars

r(kplexes) number of maximal k-plexes found meeting minsize(int)

Matrices

r(kplex_matrix) k-plexes-by-nodes 0/1 membership matrix, one row per maximal k-plex

References

Seidman, S.B., Foster, B.L. (1978). A graph-theoretic generalization of the clique concept. Journal of Mathematical Sociology 6(1), 139-154.

Bron, C., Kerbosch, J. (1973). Algorithm 457: finding all cliques of an undirected graph. Communications of the ACM 16(9), 575-577.

Wasserman, S., Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. (cliques and cohesive subgroups)

nwkplex