{ "_id": "6a1973bdacfb0bcc41defb9b", "Package": "sna", "Version": "2.8", "Date": "2024-09-07", "Title": "Tools for Social Network Analysis", "Authors@R": "person(given=c(\"Carter\", \"T.\"), family=\"Butts\", role=c(\"aut\",\"cre\",\"cph\"), email = \"buttsc@uci.edu\")", "Description": "A range of tools for social network analysis, including\nnode and graph-level indices, structural distance and\ncovariance methods, structural equivalence detection, network\nregression, random graph generation, and 2D/3D network\nvisualization.", "License": "GPL (>= 2)", "URL": "https://statnet.org", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-29 11:04:52 UTC", "User": "root" }, "Author": "Carter T. Butts [aut, cre, cph]", "Maintainer": "Carter T. Butts ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-09-09 02:57:17 UTC", "RemoteUrl": "https://github.com/cran/sna", "RemoteRef": "HEAD", "RemoteSha": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "MD5sum": "dcfc78ff84b8da400723315bf2d72f33", "_user": "cran", "_type": "src", "_file": "sna_2.8.tar.gz", "_fileid": "514c7b03865c0cbce330f696e5bc0053c04d7f72cd772665fd7ef057bdbafdb1", "_filesize": 1268707, "_sha256": "514c7b03865c0cbce330f696e5bc0053c04d7f72cd772665fd7ef057bdbafdb1", "_created": "2026-05-29T11:04:52.000Z", "_published": "2026-05-29T11:08:45.570Z", "_distro": "noble", "_jobs": [ { "job": 78488558181, "time": 165, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7289241906" }, { "job": 78488558173, "time": 133, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7289233347" }, { "job": 78488558220, "time": 163, "config": "linux-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7289241262" }, { "job": 78488558140, "time": 175, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7289244898" }, { "job": 78488113299, "time": 188, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7289195251" }, { "job": 78488558077, "time": 109, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7289226751" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/sna", "_commit": { "id": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "author": "Carter T. Butts ", "committer": "cran-robot ", "message": "version 2.8\n", "time": 1725850637 }, "_maintainer": { "name": "Carter T. Butts", "email": "buttsc@uci.edu" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.0.0", "role": "Depends" }, { "package": "utils", "role": "Depends" }, { "package": "statnet.common", "role": "Depends" }, { "package": "network", "role": "Depends" }, { "package": "rgl", "role": "Suggests" }, { "package": "numDeriv", "role": "Suggests" }, { "package": "SparseM", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 93, "_updates": [], "_tags": [], "_stars": 8, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 31367, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/sna" }, "_mentions": 67, "_searchresults": 3392, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/sna.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.3", "date": "2001-05-28" }, { "version": "0.4", "date": "2001-10-29" }, { "version": "0.41", "date": "2002-03-28" }, { "version": "0.42", "date": "2003-07-04" }, { "version": "0.43", "date": "2003-10-09" }, { "version": "0.44-1", "date": "2004-06-02" }, { "version": "0.50-1", "date": "2005-01-06" }, { "version": "0.51-0", "date": "2005-01-10" }, { "version": "1.0-0", "date": "2005-08-20" }, { "version": "1.1", "date": "2006-04-15" }, { "version": "1.2", "date": "2006-08-25" }, { "version": "1.3", "date": "2006-10-11" }, { "version": "1.4", "date": "2006-12-18" }, { "version": "1.5", "date": "2007-08-01" }, { "version": "2.0", "date": "2009-06-07" }, { "version": "2.0-1", "date": "2009-06-08" }, { "version": "2.1-0", "date": "2010-04-15" }, { "version": "2.2-0", "date": "2012-10-29" }, { "version": "2.2-1", "date": "2012-12-21" }, { "version": "2.2-2", "date": "2013-01-10" }, { "version": "2.3-1", "date": "2013-03-02" }, { "version": "2.3-2", "date": "2014-01-14" }, { "version": "2.4", "date": "2016-08-08" }, { "version": "2.5", "date": "2019-12-10" }, { "version": "2.6", "date": "2020-10-06" }, { "version": "2.7", "date": "2022-06-01" }, { "version": "2.7-1", "date": "2023-01-24" }, { "version": "2.7-2", "date": "2023-12-06" }, { "version": "2.8", "date": "2024-09-08" } ], "_exports": [ "%c%.matrix", "add.isolates", "aggarray3d_R", "as.edgelist.sna", "as.sociomatrix.sna", "bbnam", "bbnam.actor", "bbnam.bf", "bbnam.fixed", "bbnam.jntlik", "bbnam.jntlik.slice", "bbnam.pooled", "bbnam.probtie", "betweenness", "betweenness_R", "bicomponent.dist", "bicomponents_R", "blockmodel", "blockmodel.expand", "bn", "bn_cftp_R", "bn_dyadstats_R", "bn_lpl_dyad_R", "bn_lpl_triad_R", "bn_mcmc_R", "bn_ptriad_R", "bn_triadstats_R", "bn.nlpl.dyad", "bn.nlpl.edge", "bn.nlpl.triad", "bn.nltl", "bonpow", "brokerage", "brokerage_R", "centralgraph", "centralization", "clique.census", "cliques_R", "closeness", "coef.bn", "coef.lnam", "component_dist_R", "component.dist", "component.largest", "component.size.byvertex", "components", "compsizes_R", "connectedness", "connectedness_R", "consensus", "cug.test", "cugtest", "cutpoints", "cutpointsDir_R", "cutpointsUndir_R", "cycleCensus_R", "degree", "degree_R", "diag.remove", "dyad.census", "dyadcode_R", "efficiency", "ego.extract", "equiv.clust", "eval.edgeperturbation", "evcent", "evcent_R", "event2dichot", "flowbet", "gapply", "gclust.boxstats", "gclust.centralgraph", "gcor", "gcov", "gden", "gdist.plotdiff", "gdist.plotstats", "geodist", "geodist_adj_R", "geodist_R", "geodist_val_R", "gilschmidt", "gilschmidt_R", "gliop", "gplot", "gplot_layout_fruchtermanreingold_old_R", "gplot_layout_fruchtermanreingold_R", "gplot_layout_kamadakawai_R", "gplot_layout_target_R", "gplot.arrow", "gplot.layout.adj", "gplot.layout.circle", "gplot.layout.circrand", "gplot.layout.eigen", "gplot.layout.fruchtermanreingold", "gplot.layout.geodist", "gplot.layout.hall", "gplot.layout.kamadakawai", "gplot.layout.mds", "gplot.layout.princoord", "gplot.layout.random", "gplot.layout.rmds", "gplot.layout.segeo", "gplot.layout.seham", "gplot.layout.spring", "gplot.layout.springrepulse", "gplot.layout.target", "gplot.loop", "gplot.target", "gplot.vertex", "gplot3d", "gplot3d_layout_fruchtermanreingold_R", "gplot3d_layout_kamadakawai_R", "gplot3d.arrow", "gplot3d.layout.adj", "gplot3d.layout.eigen", "gplot3d.layout.fruchtermanreingold", "gplot3d.layout.geodist", "gplot3d.layout.hall", "gplot3d.layout.kamadakawai", "gplot3d.layout.mds", "gplot3d.layout.princoord", "gplot3d.layout.random", "gplot3d.layout.rmds", "gplot3d.layout.segeo", "gplot3d.layout.seham", "gplot3d.loop", "graphcent", "grecip", "gscor", "gscov", "gt", "gtrans", "gvectorize", "hdist", "hierarchy", "infocent", "interval.graph", "is.connected", "is.edgelist.sna", "is.isolate", "isolates", "kcores", "kcores_R", "kcycle.census", "kpath.census", "lab.optimize", "lab.optimize.anneal", "lab.optimize.exhaustive", "lab.optimize.gumbel", "lab.optimize.hillclimb", "lab.optimize.mc", "lnam", "loadcent", "logadd_R", "logMean", "logSub", "logsub_R", "logSum", "lower.tri.remove", "lubness", "lubness_con_R", "make.stochastic", "maxflow", "maxflow_EK_R", "mutuality", "nacf", "neighborhood", "netcancor", "netlm", "netlogit", "npostpred", "nties", "numperm", "pathCensus_R", "plot.bbnam", "plot.bbnam.actor", "plot.bbnam.fixed", "plot.bbnam.pooled", "plot.blockmodel", "plot.bn", "plot.cug.test", "plot.cugtest", "plot.equiv.clust", "plot.lnam", "plot.qaptest", "plot.sociomatrix", "potscalered.mcmc", "prestige", "print.bayes.factor", "print.bbnam", "print.bbnam.actor", "print.bbnam.fixed", "print.bbnam.pooled", "print.blockmodel", "print.bn", "print.cug.test", "print.cugtest", "print.equiv.clust", "print.lnam", "print.netcancor", "print.netlm", "print.netlogit", "print.qaptest", "print.summary.bayes.factor", "print.summary.bbnam", "print.summary.bbnam.actor", "print.summary.bbnam.fixed", "print.summary.bbnam.pooled", "print.summary.blockmodel", "print.summary.bn", "print.summary.brokerage", "print.summary.cugtest", "print.summary.lnam", "print.summary.netcancor", "print.summary.netlm", "print.summary.netlogit", "print.summary.qaptest", "pstar", "qaptest", "reachability", "reachability_R", "read.dot", "read.nos", "redist", "rewire.ud", "rewire.ws", "rgbern_R", "rgbn", "rgnm", "rgnmix", "rgraph", "rguman", "rgws", "rmperm", "rperm", "sdmat", "se.lnam", "sedist", "simmelian", "sociomatrixplot", "sr2css", "stackcount", "stresscent", "stresscent_R", "structdist", "structure.statistics", "summary.bayes.factor", "summary.bbnam", "summary.bbnam.actor", "summary.bbnam.fixed", "summary.bbnam.pooled", "summary.blockmodel", "summary.bn", "summary.brokerage", "summary.cugtest", "summary.lnam", "summary.netcancor", "summary.netlm", "summary.netlogit", "summary.qaptest", "symmetrize", "transitivity_R", "triad_census_R", "triad_classify_R", "triad.census", "triad.classify", "udrewire_R", "undirComponents_R", "upper.tri.remove", "write.dl", "write.nos", "wsrewire_R" ], "_datasets": [ { "name": "coleman", "title": "Coleman's High School Friendship Data", "object": "coleman", "file": "coleman.RData", "class": [ "array" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "add.isolates", "title": "Add Isolates to a Graph", "topics": [ "add.isolates" ] }, { "page": "bbnam", "title": "Butts' (Hierarchical) Bayesian Network Accuracy Model", "topics": [ "bbnam", "bbnam.actor", "bbnam.fixed", "bbnam.pooled" ] }, { "page": "bbnam.bf", "title": "Estimate Bayes Factors for the bbnam", "topics": [ "bbnam.bf" ] }, { "page": "betweenness", "title": "Compute the Betweenness Centrality Scores of Network Positions", "topics": [ "betweenness", "betweenness_R" ] }, { "page": "bicomponent.dist", "title": "Calculate the Bicomponents of a Graph", "topics": [ "bicomponent.dist", "bicomponents_R" ] }, { "page": "blockmodel", "title": "Generate Blockmodels Based on Partitions of Network Positions", "topics": [ "blockmodel" ] }, { "page": "blockmodel.expand", "title": "Generate a Graph (or Stack) from a Given Blockmodel Using Particular Expansion Rules", "topics": [ "blockmodel.expand" ] }, { "page": "bn", "title": "Fit a Biased Net Model", "topics": [ "bn", "bn.nlpl.dyad", "bn.nlpl.edge", "bn.nlpl.triad", "bn.nltl", "bn_dyadstats_R", "bn_lpl_dyad_R", "bn_lpl_triad_R", "bn_ptriad_R", "bn_triadstats_R", "coef.bn", "plot.bn", "print.bn", "print.summary.bn", "summary.bn" ] }, { "page": "bonpow", "title": "Find Bonacich Power Centrality Scores of Network Positions", "topics": [ "bonpow" ] }, { "page": "brokerage", "title": "Perform a Gould-Fernandez Brokerage Analysis", "topics": [ "brokerage", "brokerage_R", "print.summary.brokerage", "summary.brokerage" ] }, { "page": "centralgraph", "title": "Find the Central Graph of a Labeled Graph Stack", "topics": [ "centralgraph" ] }, { "page": "centralization", "title": "Find the Centralization of a Given Network, for Some Measure of Centrality", "topics": [ "centralization" ] }, { "page": "clique.census", "title": "Compute Cycle Census Information", "topics": [ "clique.census", "cliques_R" ] }, { "page": "closeness", "title": "Compute the Closeness Centrality Scores of Network Positions", "topics": [ "closeness" ] }, { "page": "coleman", "title": "Coleman's High School Friendship Data", "topics": [ "coleman" ] }, { "page": "component.dist", "title": "Calculate the Component Size Distribution of a Graph", "topics": [ "component.dist", "component.largest", "component_dist_R", "undirComponents_R" ] }, { "page": "component.size.byvertex", "title": "Get Component Sizes, by Vertex", "topics": [ "component.size.byvertex", "compsizes_R" ] }, { "page": "components", "title": "Find the Number of (Maximal) Components Within a Given Graph", "topics": [ "components" ] }, { "page": "connectedness", "title": "Compute Graph Connectedness Scores", "topics": [ "connectedness", "connectedness_R" ] }, { "page": "consensus", "title": "Estimate a Consensus Structure from Multiple Observations", "topics": [ "consensus" ] }, { "page": "cug.test", "title": "Univariate Conditional Uniform Graph Tests", "topics": [ "cug.test", "plot.cug.test", "print.cug.test" ] }, { "page": "cugtest", "title": "Perform Conditional Uniform Graph (CUG) Hypothesis Tests for Graph-Level Indices", "topics": [ "cugtest" ] }, { "page": "cutpoints", "title": "Identify the Cutpoints of a Graph or Digraph", "topics": [ "cutpoints", "cutpointsDir_R", "cutpointsUndir_R" ] }, { "page": "degree", "title": "Compute the Degree Centrality Scores of Network Positions", "topics": [ "degree", "degree_R" ] }, { "page": "diag.remove", "title": "Remove the Diagonals of Adjacency Matrices in a Graph Stack", "topics": [ "diag.remove" ] }, { "page": "dyad.census", "title": "Compute a Holland and Leinhardt MAN Dyad Census", "topics": [ "dyad.census" ] }, { "page": "efficiency", "title": "Compute Graph Efficiency Scores", "topics": [ "efficiency" ] }, { "page": "ego.extract", "title": "Extract Egocentric Networks from Complete Network Data", "topics": [ "ego.extract" ] }, { "page": "equiv.clust", "title": "Find Clusters of Positions Based on an Equivalence Relation", "topics": [ "equiv.clust", "print.equiv.clust" ] }, { "page": "eval.edgeperturbation", "title": "Compute the Effects of Single-Edge Perturbations on Structural Indices", "topics": [ "eval.edgeperturbation" ] }, { "page": "evcent", "title": "Find Eigenvector Centrality Scores of Network Positions", "topics": [ "evcent", "evcent_R" ] }, { "page": "event2dichot", "title": "Convert an Observed Event Matrix to a Dichotomous matrix", "topics": [ "event2dichot" ] }, { "page": "flowbet", "title": "Calculate Flow Betweenness Scores of Network Positions", "topics": [ "flowbet" ] }, { "page": "gapply", "title": "Apply Functions Over Vertex Neighborhoods", "topics": [ "gapply" ] }, { "page": "gclust.boxstats", "title": "Plot Statistics Associated with Graph Clusters", "topics": [ "gclust.boxstats" ] }, { "page": "gclust.centralgraph", "title": "Get Central Graphs Associated with Graph Clusters", "topics": [ "gclust.centralgraph" ] }, { "page": "gcor", "title": "Find the (Product-Moment) Correlation Between Two or More Labeled Graphs", "topics": [ "gcor" ] }, { "page": "gcov", "title": "Find the Covariance(s) Between Two or More Labeled Graphs", "topics": [ "gcov" ] }, { "page": "gden", "title": "Find the Density of a Graph", "topics": [ "gden" ] }, { "page": "gdist.plotdiff", "title": "Plot Differences in Graph-level Statistics Against Inter-graph Distances", "topics": [ "gdist.plotdiff" ] }, { "page": "gdist.plotstats", "title": "Plot Various Graph Statistics Over a Network MDS", "topics": [ "gdist.plotstats" ] }, { "page": "geodist", "title": "Fund the Numbers and Lengths of Geodesics Among Nodes in a Graph", "topics": [ "geodist", "geodist_adj_R", "geodist_R", "geodist_val_R" ] }, { "page": "gilschmidt", "title": "Compute the Gil-Schmidt Power Index", "topics": [ "gilschmidt", "gilschmidt_R" ] }, { "page": "gliop", "title": "Return a Binary Operation on GLI Values Computed on Two Graphs", "topics": [ "gliop" ] }, { "page": "gplot", "title": "Two-Dimensional Visualization of Graphs", "topics": [ "gplot" ] }, { "page": "gplot.arrow", "title": "Add Arrows or Segments to a Plot", "topics": [ "gplot.arrow" ] }, { "page": "gplot.layout", "title": "Vertex Layout Functions for gplot", "topics": [ "gplot.layout", "gplot.layout.adj", "gplot.layout.circle", "gplot.layout.circrand", "gplot.layout.eigen", "gplot.layout.fruchtermanreingold", "gplot.layout.geodist", "gplot.layout.hall", "gplot.layout.kamadakawai", "gplot.layout.mds", "gplot.layout.princoord", "gplot.layout.random", "gplot.layout.rmds", "gplot.layout.segeo", "gplot.layout.seham", "gplot.layout.spring", "gplot.layout.springrepulse", "gplot.layout.target", "gplot_layout_fruchtermanreingold_old_R", "gplot_layout_fruchtermanreingold_R", "gplot_layout_kamadakawai_R" ] }, { "page": "gplot.loop", "title": "Add Loops to a Plot", "topics": [ "gplot.loop" ] }, { "page": "gplot.target", "title": "Display a Graph in Target Diagram Form", "topics": [ "gplot.target", "gplot_layout_target_R" ] }, { "page": "gplot.vertex", "title": "Add Vertices to a Plot", "topics": [ "gplot.vertex" ] }, { "page": "gplot3d", "title": "Three-Dimensional Visualization of Graphs", "topics": [ "gplot3d" ] }, { "page": "gplot3d.arrow", "title": "Add Arrows a Three-Dimensional Plot", "topics": [ "gplot3d.arrow" ] }, { "page": "gplot3d.layout", "title": "Vertex Layout Functions for gplot3d", "topics": [ "gplot3d.layout", "gplot3d.layout.adj", "gplot3d.layout.eigen", "gplot3d.layout.fruchtermanreingold", "gplot3d.layout.geodist", "gplot3d.layout.hall", "gplot3d.layout.kamadakawai", "gplot3d.layout.mds", "gplot3d.layout.princoord", "gplot3d.layout.random", "gplot3d.layout.rmds", "gplot3d.layout.segeo", "gplot3d.layout.seham", "gplot3d_layout_fruchtermanreingold_R", "gplot3d_layout_kamadakawai_R" ] }, { "page": "gplot3d.loop", "title": "Add Loops to a Three-Dimensional Plot", "topics": [ "gplot3d.loop" ] }, { "page": "graphcent", "title": "Compute the (Harary) Graph Centrality Scores of Network Positions", "topics": [ "graphcent" ] }, { "page": "grecip", "title": "Compute the Reciprocity of an Input Graph or Graph Stack", "topics": [ "grecip" ] }, { "page": "gscor", "title": "Find the Structural Correlations Between Two or More Graphs", "topics": [ "gscor" ] }, { "page": "gscov", "title": "Find the Structural Covariance(s) Between Two or More Graphs", "topics": [ "gscov" ] }, { "page": "gt", "title": "Transpose an Input Graph", "topics": [ "gt" ] }, { "page": "gtrans", "title": "Compute the Transitivity of an Input Graph or Graph Stack", "topics": [ "gtrans", "transitivity_R" ] }, { "page": "gvectorize", "title": "Vectorization of Adjacency Matrices", "topics": [ "gvectorize" ] }, { "page": "hdist", "title": "Find the Hamming Distances Between Two or More Graphs", "topics": [ "hdist" ] }, { "page": "hierarchy", "title": "Compute Graph Hierarchy Scores", "topics": [ "hierarchy" ] }, { "page": "infocent", "title": "Find Information Centrality Scores of Network Positions", "topics": [ "infocent" ] }, { "page": "interval.graph", "title": "Convert Spell Data to Interval Graphs", "topics": [ "interval.graph" ] }, { "page": "is.connected", "title": "Is a Given Graph Connected?", "topics": [ "is.connected" ] }, { "page": "is.isolate", "title": "Is Ego an Isolate?", "topics": [ "is.isolate" ] }, { "page": "isolates", "title": "List the Isolates in a Graph or Graph Stack", "topics": [ "isolates" ] }, { "page": "kcores", "title": "Compute the k-Core Structure of a Graph", "topics": [ "kcores", "kcores_R" ] }, { "page": "path.census", "title": "Compute Path or Cycle Census Information", "topics": [ "cycleCensus_R", "kcycle.census", "kpath.census", "pathCensus_R" ] }, { "page": "lab.optimize", "title": "Optimize a Bivariate Graph Statistic Across a Set of Accessible Permutations", "topics": [ "lab.optimize", "lab.optimize.anneal", "lab.optimize.exhaustive", "lab.optimize.gumbel", "lab.optimize.hillclimb", "lab.optimize.mc" ] }, { "page": "lnam", "title": "Fit a Linear Network Autocorrelation Model", "topics": [ "coef.lnam", "lnam", "se.lnam" ] }, { "page": "loadcent", "title": "Compute the Load Centrality Scores of Network Positions", "topics": [ "loadcent" ] }, { "page": "lower.tri.remove", "title": "Remove the Lower Triangles of Adjacency Matrices in a Graph Stack", "topics": [ "lower.tri.remove" ] }, { "page": "lubness", "title": "Compute Graph LUBness Scores", "topics": [ "lubness", "lubness_con_R" ] }, { "page": "make.stochastic", "title": "Make a Graph Stack Row, Column, or Row-column Stochastic", "topics": [ "make.stochastic" ] }, { "page": "maxflow", "title": "Calculate Maximum Flows Between Vertices", "topics": [ "maxflow", "maxflow_EK_R" ] }, { "page": "mutuality", "title": "Find the Mutuality of a Graph", "topics": [ "mutuality" ] }, { "page": "nacf", "title": "Sample Network Covariance and Correlation Functions", "topics": [ "nacf" ] }, { "page": "neighborhood", "title": "Compute Neighborhood Structures of Specified Order", "topics": [ "neighborhood" ] }, { "page": "netcancor", "title": "Canonical Correlation for Labeled Graphs", "topics": [ "netcancor" ] }, { "page": "netlm", "title": "Linear Regression for Network Data", "topics": [ "netlm" ] }, { "page": "netlogit", "title": "Logistic Regression for Network Data", "topics": [ "netlogit" ] }, { "page": "npostpred", "title": "Take Posterior Predictive Draws for Functions of Networks", "topics": [ "npostpred" ] }, { "page": "nties", "title": "Find the Number of Possible Ties in a Given Graph or Graph Stack", "topics": [ "nties" ] }, { "page": "numperm", "title": "Get the nth Permutation Vector by Periodic Placement", "topics": [ "numperm" ] }, { "page": "plot.bbnam", "title": "Plotting for bbnam Objects", "topics": [ "plot.bbnam", "plot.bbnam.actor", "plot.bbnam.fixed", "plot.bbnam.pooled" ] }, { "page": "plot.blockmodel", "title": "Plotting for blockmodel Objects", "topics": [ "plot.blockmodel" ] }, { "page": "plot.cugtest", "title": "Plotting for cugtest Objects", "topics": [ "plot.cugtest" ] }, { "page": "plot.equiv.clust", "title": "Plot an equiv.clust Object", "topics": [ "plot.equiv.clust" ] }, { "page": "plot.lnam", "title": "Plotting for lnam Objects", "topics": [ "plot.lnam" ] }, { "page": "plot.qaptest", "title": "Plotting for qaptest Objects", "topics": [ "plot.qaptest" ] }, { "page": "plot.sociomatrix", "title": "Plot Matrices Using a Color/Intensity Grid", "topics": [ "plot.sociomatrix", "sociomatrixplot" ] }, { "page": "potscalered.mcmc", "title": "Compute Gelman and Rubin's Potential Scale Reduction Measure for a Markov Chain Monte Carlo Simulation", "topics": [ "potscalered.mcmc" ] }, { "page": "prestige", "title": "Calculate the Vertex Prestige Scores", "topics": [ "prestige" ] }, { "page": "print.bayes.factor", "title": "Printing for Bayes Factor Objects", "topics": [ "print.bayes.factor" ] }, { "page": "print.bbnam", "title": "Printing for bbnam Objects", "topics": [ "print.bbnam", "print.bbnam.actor", "print.bbnam.fixed", "print.bbnam.pooled" ] }, { "page": "print.blockmodel", "title": "Printing for blockmodel Objects", "topics": [ "print.blockmodel" ] }, { "page": "print.cugtest", "title": "Printing for cugtest Objects", "topics": [ "print.cugtest" ] }, { "page": "print.lnam", "title": "Printing for lnam Objects", "topics": [ "print.lnam" ] }, { "page": "print.netcancor", "title": "Printing for netcancor Objects", "topics": [ "print.netcancor" ] }, { "page": "print.netlm", "title": "Printing for netlm Objects", "topics": [ "print.netlm" ] }, { "page": "print.netlogit", "title": "Printing for netlogit Objects", "topics": [ "print.netlogit" ] }, { "page": "print.qaptest", "title": "Printing for qaptest Objects", "topics": [ "print.qaptest" ] }, { "page": "print.summary.bayes.factor", "title": "Printing for summary.bayes.factor Objects", "topics": [ "print.summary.bayes.factor" ] }, { "page": "print.summary.bbnam", "title": "Printing for summary.bbnam Objects", "topics": [ "print.summary.bbnam", "print.summary.bbnam.actor", "print.summary.bbnam.fixed", "print.summary.bbnam.pooled" ] }, { "page": "print.summary.blockmodel", "title": "Printing for summary.blockmodel Objects", "topics": [ "print.summary.blockmodel" ] }, { "page": "print.summary.cugtest", "title": "Printing for summary.cugtest Objects", "topics": [ "print.summary.cugtest" ] }, { "page": "print.summary.lnam", "title": "Printing for summary.lnam Objects", "topics": [ "print.summary.lnam" ] }, { "page": "print.summary.netcancor", "title": "Printing for summary.netcancor Objects", "topics": [ "print.summary.netcancor" ] }, { "page": "print.summary.netlm", "title": "Printing for summary.netlm Objects", "topics": [ "print.summary.netlm" ] }, { "page": "print.summary.netlogit", "title": "Printing for summary.netlogit Objects", "topics": [ "print.summary.netlogit" ] }, { "page": "print.summary.qaptest", "title": "Printing for summary.qaptest Objects", "topics": [ "print.summary.qaptest" ] }, { "page": "pstar", "title": "Fit a p*/ERG Model Using a Logistic Approximation", "topics": [ "pstar" ] }, { "page": "qaptest", "title": "Perform Quadratic Assignment Procedure (QAP) Hypothesis Tests for Graph-Level Statistics", "topics": [ "qaptest" ] }, { "page": "reachability", "title": "Find the Reachability Matrix of a Graph", "topics": [ "reachability", "reachability_R" ] }, { "page": "read.dot", "title": "Read Graphviz DOT Files", "topics": [ "read.dot" ] }, { "page": "read.nos", "title": "Read (N)eo-(O)rg(S)tat Input Files", "topics": [ "read.nos" ] }, { "page": "redist", "title": "Find a Matrix of Distances Between Positions Based on Regular Equivalence", "topics": [ "redist" ] }, { "page": "rgbn", "title": "Draw from a Skvoretz-Fararo Biased Net Process", "topics": [ "bn_cftp_R", "bn_mcmc_R", "rgbn" ] }, { "page": "rgnm", "title": "Draw Density-Conditioned Random Graphs", "topics": [ "rgnm" ] }, { "page": "rgnmix", "title": "Draw Mixing-Conditioned Random Graphs", "topics": [ "rgnmix" ] }, { "page": "rgraph", "title": "Generate Bernoulli Random Graphs", "topics": [ "rgbern_R", "rgraph" ] }, { "page": "rguman", "title": "Draw Dyad Census-Conditioned Random Graphs", "topics": [ "rguman" ] }, { "page": "rgws", "title": "Draw From the Watts-Strogatz Rewiring Model", "topics": [ "rewire.ud", "rewire.ws", "rgws", "udrewire_R", "wsrewire_R" ] }, { "page": "rmperm", "title": "Randomly Permute the Rows and Columns of an Input Matrix", "topics": [ "rmperm" ] }, { "page": "rperm", "title": "Draw a Random Permutation Vector with Exchangeability Constraints", "topics": [ "rperm" ] }, { "page": "sdmat", "title": "Estimate the Structural Distance Matrix for a Graph Stack", "topics": [ "sdmat" ] }, { "page": "sedist", "title": "Find a Matrix of Distances Between Positions Based on Structural Equivalence", "topics": [ "sedist" ] }, { "page": "simmelian", "title": "Find the Simmelian Tie Structure of a Graph", "topics": [ "simmelian" ] }, { "page": "sna", "title": "Tools for Social Network Analysis", "topics": [ "sna" ] }, { "page": "sna-coercion", "title": "sna Coercion Functions", "topics": [ "as.edgelist.sna", "as.sociomatrix.sna", "is.edgelist.sna" ] }, { "page": "sna-deprecated", "title": "Deprecated Functions in sna Package", "topics": [ "sna-deprecated" ] }, { "page": "sna.operators", "title": "Graphical Operators", "topics": [ "%c%.matrix", "sna.operators" ] }, { "page": "sr2css", "title": "Convert a Row-wise Self-Report Matrix to a CSS Matrix with Missing Observations", "topics": [ "sr2css" ] }, { "page": "stackcount", "title": "How Many Graphs are in a Graph Stack?", "topics": [ "stackcount" ] }, { "page": "stresscent", "title": "Compute the Stress Centrality Scores of Network Positions", "topics": [ "stresscent", "stresscent_R" ] }, { "page": "structdist", "title": "Find the Structural Distances Between Two or More Graphs", "topics": [ "structdist" ] }, { "page": "structure.statistics", "title": "Compute Network Structure Statistics", "topics": [ "structure.statistics" ] }, { "page": "summary.bayes.factor", "title": "Detailed Summaries of Bayes Factor Objects", "topics": [ "summary.bayes.factor" ] }, { "page": "summary.bbnam", "title": "Detailed Summaries of bbnam Objects", "topics": [ "summary.bbnam", "summary.bbnam.actor", "summary.bbnam.fixed", "summary.bbnam.pooled" ] }, { "page": "summary.blockmodel", "title": "Detailed Summaries of blockmodel Objects", "topics": [ "summary.blockmodel" ] }, { "page": "summary.cugtest", "title": "Detailed Summaries of cugtest Objects", "topics": [ "summary.cugtest" ] }, { "page": "summary.lnam", "title": "Detailed Summaries of lnam Objects", "topics": [ "summary.lnam" ] }, { "page": "summary.netcancor", "title": "Detailed Summaries of netcancor Objects", "topics": [ "summary.netcancor" ] }, { "page": "summary.netlm", "title": "Detailed Summaries of netlm Objects", "topics": [ "summary.netlm" ] }, { "page": "summary.netlogit", "title": "Detailed Summaries of netlogit Objects", "topics": [ "summary.netlogit" ] }, { "page": "summary.qaptest", "title": "Detailed Summaries of qaptest Objects", "topics": [ "summary.qaptest" ] }, { "page": "symmetrize", "title": "Symmetrize an Adjacency Matrix", "topics": [ "symmetrize" ] }, { "page": "triad.census", "title": "Compute the Davis and Leinhardt Triad Census", "topics": [ "triad.census", "triad_census_R" ] }, { "page": "triad.classify", "title": "Compute the Davis and Leinhardt Classification of a Given Triad", "topics": [ "triad.classify", "triad_classify_R" ] }, { "page": "upper.tri.remove", "title": "Remove the Upper Triangles of Adjacency Matrices in a Graph Stack", "topics": [ "upper.tri.remove" ] }, { "page": "write.dl", "title": "Write Output Graphs in DL Format", "topics": [ "write.dl" ] }, { "page": "write.nos", "title": "Write Output Graphs in (N)eo-(O)rg(S)tat Format", "topics": [ "write.nos" ] } ], "_rundeps": [ "cli", "coda", "glue", "lattice", "lifecycle", "magrittr", "Matrix", "network", "pillar", "pkgconfig", "rlang", "statnet.common", "tibble", "utf8", "vctrs" ], "_score": 9.375623017777517, "_indexed": true, "_nocasepkg": "sna", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.8", "date": "2026-05-29T11:07:30.000Z", "distro": "noble", "arch": "aarch64", "commit": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "fileid": "0c555e381f762d69bf6752ff46ce2a350fb6e3c80edc0e189d823e504cb3671e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142" }, { "r": "4.7.0", "os": "linux", "version": "2.8", "date": "2026-05-29T11:06:57.000Z", "distro": "noble", "arch": "x86_64", "commit": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "fileid": "4638435132ebaa9f3d47e814b40503d8279e85dea3818f0f67727ea99fd3a7cc", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142" }, { "r": "4.6.0", "os": "linux", "version": "2.8", "date": "2026-05-29T11:07:25.000Z", "distro": "noble", "arch": "aarch64", "commit": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "fileid": "cb7e235cf10ca9cfdb0f6f2bc257b7943200454769f9b6caf392c99945b1a47e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142" }, { "r": "4.6.0", "os": "linux", "version": "2.8", "date": "2026-05-29T11:07:26.000Z", "distro": "noble", "arch": "x86_64", "commit": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "fileid": "be4767c7d6e2f0f6f2c6ed326251454e00c1dc30e96fa70db3d4fde0052e1bab", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142" }, { "r": "4.6.0", "os": "wasm", "version": "2.8", "date": "2026-05-29T11:07:16.000Z", "arch": "emscripten", "commit": "7526f188e06d3340eb9279d4d8dff5b6dc9022b9", "fileid": "a14a0ce74dfa321338eaaa21720b44066a7107371727802a6b9dd2dc9141916d", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/26633555142" } ] }