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A B C D E G H I L M N P Q R S T U
| %c% | Graphical Operators |
| addisolates | Add Isolates to a Graph |
| bbnam | Butts' (Hierarchical) Bayesian Network Accuracy Model |
| bbnam.bf | Estimate Bayes Factors for the bbnam |
| bbnam.fixed | Butts' (Hierarchical) Bayesian Network Accuracy Model |
| bbnam.pooled | Butts' (Hierarchical) Bayesian Network Accuracy Model |
| betweenness | Compute the Betweenness Centrality Scores of Network Positions |
| blockmodel | Generate Blockmodels Based on Partitions of Network Positions |
| blockmodel.expand | Generate a Graph (or Stack) from a Given Blockmodel Using Particular Expansion Rules |
| bonpow | Find Bonacich Power Centrality Scores of Network Positions |
| centralgraph | Find the Central Graph of a Labeled Graph Set |
| centralization | Find the Centralization of a Given Network, for Some Measure of Centrality |
| closeness | Compute the Closeness Centrality Scores of Network Positions |
| coef.lnam | Fit a Linear Network Autocorrelation Model |
| component.dist | Calculate the Component Size Distribution of a Graph |
| components | Find the Number of (Maximal) Components Within a Given Graph |
| connectedness | Compute Graph Connectedness Scores |
| consensus | Estimate a Consensus Structure from Multiple Observations |
| cugtest | Perform Conditional Uniform Graph (CUG) Hypothesis Tests for Graph-Level Indices |
| degree | Compute the Degree Centrality Scores of Network Positions |
| diag.remove | Remove the Diagonals of Adjacency Matrices in a Graph Stack |
| dyad.census | Compute a Holland and Leinhardt MAN Dyad Census |
| efficiency | Compute Graph Efficiency Scores |
| equiv.clust | Find Clusters of Positions Based on an Equivalence Relation |
| eval.edgeperturbation | Compute the Effects of Single-Edge Perturbations on Structural Indices |
| evcent | Find Eigenvector Centrality Scores of Network Positions |
| event2dichot | Convert an Observed Event Matrix to a Dichotomous matrix |
| gapply | Apply Functions Over Vertex Neighborhoods |
| gclust.boxstats | Plot Statistics Associated with Graph Clusters |
| gclust.centralgraph | Get Central Graphs Associated with Graph Clusters |
| gcor | Find the (Product-Moment) Correlation Between Two or More Labeled Graphs |
| gcov | Find the Covariance(s) Between Two or More Labeled Graphs |
| gden | Find the Density of a Graph |
| gdist.plotdiff | Plot Differences in Graph-level Statistics Against Inter-graph Distances |
| gdist.plotstats | Plot Various Graph Statistics Over a Network MDS |
| geodist | Fund the Numbers and Lengths of Geodesics Among Nodes in a Graph |
| gliop | Return a Binary Operation on GLI Values Computed on Two Graphs |
| gplot | Two-Dimensional Visualization of Graphs |
| gplot.layout | Vertex Layout Functions for gplot |
| graphcent | Compute the (Harary) Graph Centrality Scores of Network Positions |
| grecip | Compute the Reciprocity of an Input Graph or Graph Stack |
| gscor | Find the Structural Correlations Between Two or More Graphs |
| gscov | Find the Structural Covariance(s) Between Two or More Graphs |
| gtrans | Compute the Transitivity of an Input Graph or Graph Stack |
| gvectorize | Vectorization of Adjacency Matrices |
| hdist | Find the Hamming Distances Between Two or More Graphs |
| hierarchy | Compute Graph Hierarchy Scores |
| infocent | Find Information Centrality Scores of Network Positions |
| interval.graph | Convert Spell Data to Interval Graphs |
| is.isolate | Is Ego an Isolate? |
| isolates | List the Isolates in a Graph or Graph Stack |
| lab.optimize | Optimize a Bivariate Graph Statistic Across a Set of Accessible Permutations |
| lnam | Fit a Linear Network Autocorrelation Model |
| lower.tri.remove | Remove the Lower Triangles of Adjacency Matrices in a Graph Stack |
| lubness | Compute Graph LUBness Scores |
| make.stochastic | Make a Graph Stack Row, Column, or Row-column Stochastic |
| mutuality | Find the Mutuality of a Graph |
| netcancor | Canonical Correlation for Labeled Graphs |
| netlm | Linear Regression for Network Data |
| netlogit | Logistic Regression for Network Data |
| npostpred | Take Posterior Predictive Draws for Functions of Networks |
| nties | Find the Number of Possible Ties in a Given Graph or Stack |
| numperm | Get the nth Permutation Vector by Periodic Placement |
| plot.bbnam | Plotting for bbnam Objects |
| plot.blockmodel | Plotting for blockmodel Objects |
| plot.cugtest | Plotting for cugtest Objects |
| plot.equiv.clust | Plot an equiv.clust Object |
| plot.lnam | Plotting for lnam Objects |
| plot.qaptest | Plotting for qaptest Objects |
| plot.sociomatrix | Plot Matrices Using a Color/Intensity Grid |
| potscalered.mcmc | Compute Gelman and Rubin's Potential Scale Reduction Measure for a Markov Chain Monte Carlo Simulation |
| prestige | Calculate the Vertex Prestige Scores |
| print.bayes.factor | Printing for Bayes Factor Objects |
| print.bbnam | Printing for bbnam Objects |
| print.blockmodel | Printing for blockmodel Objects |
| print.cugtest | Printing for cugtest Objects |
| print.lnam | Printing for lnam Objects |
| print.netcancor | Printing for netcancor Objects |
| print.netlm | Printing for netlm Objects |
| print.netlogit | Printing for netlogit Objects |
| print.qaptest | Printing for qaptest Objects |
| print.summary.bayes.factor | Printing for summary.bayes.factor Objects |
| print.summary.bbnam | Printing for summary.bbnam Objects |
| print.summary.blockmodel | Printing for summary.blockmodel Objects |
| print.summary.cugtest | Printing for summary.cugtest Objects |
| print.summary.lnam | Printing for summary.lnam Objects |
| print.summary.netcancor | Printing for summary.netcancor Objects |
| print.summary.netlm | Printing for summary.netlm Objects |
| print.summary.netlogit | Printing for summary.netlogit Objects |
| print.summary.qaptest | Printing for summary.qaptest Objects |
| pstar | Fit a p*/ERG Model Using a Logistic Approximation |
| qaptest | Perform Quadratic Assignment Procedure (QAP) Hypothesis Tests for Graph-Level Statistics |
| reachability | Find the Reachability Matrix of a Graph |
| read.nos | Read (N)eo-(O)rg(S)tat Input Files |
| rgraph | Generate Bernoulli Random Graphs |
| rmperm | Randomly Permute the Rows and Columns of an Input Matrix |
| rperm | Draw a Random Permutation Vector with Exchangeability Constraints |
| sdmat | Estimate the Structural Distance Matrix for a Graph Set |
| se.lnam | Fit a Linear Network Autocorrelation Model |
| sedist | Find a Matrix of Distances Between Positions Based on Structural Equivalence |
| sna.operators | Graphical Operators |
| sr2css | Convert a Row-wise Self-Report Matrix to a CSS Matrix with Missing Observations |
| stackcount | How Many Graphs are in a Graph Stack? |
| stresscent | Compute the Stress Centrality Scores of Network Positions |
| structdist | Find the Structural Distances Between Two or More Graphs |
| summary.bayes.factor | Detailed Summaries of Bayes Factor Objects |
| summary.bbnam | Detailed Summaries of bbnam Objects |
| summary.blockmodel | Detailed Summaries of blockmodel Objects |
| summary.cugtest | Detailed Summaries of cugtest Objects |
| summary.lnam | Detailed Summaries of lnam Objects |
| summary.netcancor | Detailed Summaries of netcancor Objects |
| summary.netlm | Detailed Summaries of netlm Objects |
| summary.netlogit | Detailed Summaries of netlogit Objects |
| summary.qaptest | Detailed Summaries of qaptest Objects |
| symmetrize | Symmetrize an Adjacency Matrix |
| triad.census | Compute the Davis and Leinhardt Triad Census |
| triad.classify | Compute the Davis and Leinhardt Classification of a Given Triad |
| upper.tri.remove | Remove the Upper Triangles of Adjacency Matrices in a Graph Stack |