# Fit, Simulate and Diagnose Exponential-Family Models for Networks

## Documentation for package ‘ergm’ version 4.8.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M N O P R S T U V W misc

## -- A --

absdiff-ergmTerm | Absolute difference in nodal attribute
absdiffcat-ergmTerm | Categorical absolute difference in nodal attribute
AIC.ergm | A 'logLik()' method for 'ergm' fits.
altkstar-ergmTerm | Alternating k-star
anova.ergm | ANOVA for ERGM Fits
anova.ergmlist | ANOVA for ERGM Fits
anyNA.ergm | Exponential-Family Random Graph Models
approx.hotelling.diff.test | Approximate Hotelling T^2-Test for One or Two Population Means
as.network.numeric | Create a Simple Random network of a Given Size
asymmetric-ergmTerm | Asymmetric dyads
atleast-ergmTerm | Number of dyads with values greater than or equal to a threshold
atmost-ergmTerm | Number of dyads with values less than or equal to a threshold
attr | Specifying nodal attributes and their levels
attrcov-ergmTerm | Edge covariate by attribute pairing
attrname | Specifying nodal attributes and their levels
attrs | Specifying nodal attributes and their levels

## -- B --

B-ergmTerm | Wrap binary terms for use in valued models
b1concurrent-ergmTerm | Concurrent node count for the first mode in a bipartite network
b1cov-ergmTerm | Main effect of a covariate for the first mode in a bipartite network
b1covrange-ergmTerm | Range of covariate values for neighbors of a mode-1 node
b1degrange-ergmTerm | Degree range for the first mode in a bipartite network
b1degree-ergmTerm | Degree for the first mode in a bipartite network
b1degrees-ergmConstraint | Preserve the actor degree for bipartite networks
b1dsp-ergmTerm | Dyadwise shared partners for dyads in the first bipartition
b1factor-ergmTerm | Factor attribute effect for the first mode in a bipartite network
b1factordistinct-ergmTerm | Number of distinct neighbor types for the first node
b1mindegree-ergmTerm | Minimum degree for the first mode in a bipartite network
b1nodematch-ergmTerm | Nodal attribute-based homophily effect for the first mode in a bipartite network
b1sociality-ergmTerm | Degree
b1star-ergmTerm | k-stars for the first mode in a bipartite network
b1starmix-ergmTerm | Mixing matrix for k-stars centered on the first mode of a bipartite network
b1twostar-ergmTerm | Two-star census for central nodes centered on the first mode of a bipartite network
b2concurrent-ergmTerm | Concurrent node count for the second mode in a bipartite network
b2cov-ergmTerm | Main effect of a covariate for the second mode in a bipartite network
b2covrange-ergmTerm | Range of covariate values for neighbors of a mode-2 node
b2degrange-ergmTerm | Degree range for the second mode in a bipartite network
b2degree-ergmTerm | Degree for the second mode in a bipartite network
b2degrees-ergmConstraint | Preserve the receiver degree for bipartite networks
b2dsp-ergmTerm | Dyadwise shared partners for dyads in the second bipartition
b2factor-ergmTerm | Factor attribute effect for the second mode in a bipartite network
b2factordistinct-ergmTerm | Number of distinct neighbor types for the second mode
b2mindegree-ergmTerm | Minimum degree for the second mode in a bipartite network
b2nodematch-ergmTerm | Nodal attribute-based homophily effect for the second mode in a bipartite network
b2sociality-ergmTerm | Degree
b2star-ergmTerm | k-stars for the second mode in a bipartite network
b2starmix-ergmTerm | Mixing matrix for k-stars centered on the second mode of a bipartite network
b2twostar-ergmTerm | Two-star census for central nodes centered on the second mode of a bipartite network
balance-ergmTerm | Balanced triads
bd-ergmConstraint | Constrain maximum and minimum vertex degree
Bernoulli-ergmReference | Bernoulli reference
BIC.ergm | A 'logLik()' method for 'ergm' fits.
blockdiag-ergmConstraint | Block-diagonal structure constraint
blocks-ergmConstraint | Constrain blocks of dyads defined by mixing type on a vertex attribute.
by | Specifying nodal attributes and their levels

## -- C --

check.ErgmTerm | Ensures an Ergm Term and its Arguments Meet Appropriate Conditions
cohab | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent
cohab_MixMat | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent
cohab_PopWts | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent
cohab_TargetStats | Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent
coincidence-ergmTerm | Coincident node count for the second mode in a bipartite (aka two-mode) network
COLLAPSE_SMALLEST | Specifying nodal attributes and their levels
concurrent-ergmTerm | Concurrent node count
concurrentties-ergmTerm | Concurrent tie count
constraints-ergm | Sample Space Constraints for Exponential-Family Random Graph Models
constraints.ergm | Sample Space Constraints for Exponential-Family Random Graph Models
control.ergm | Auxiliary function for fine-tuning ERGM fitting.
control.ergm.bridge | Auxiliaries for Controlling 'ergm.bridge.llr()' and 'logLik.ergm()'
control.gof | Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation
control.gof.ergm | Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation
control.gof.formula | Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation
control.logLik.ergm | Auxiliaries for Controlling 'ergm.bridge.llr()' and 'logLik.ergm()'
control.san | Auxiliary for Controlling SAN
control.simulate | Auxiliary for Controlling ERGM Simulation
control.simulate.ergm | Auxiliary for Controlling ERGM Simulation
control.simulate.formula | Auxiliary for Controlling ERGM Simulation
control.simulate.formula.ergm | Auxiliary for Controlling ERGM Simulation
ctriad-ergmTerm | Cyclic triples
ctriple-ergmTerm | Cyclic triples
Curve-ergmTerm | Impose a curved structure on term parameters
cycle-ergmTerm | k-Cycle Census
cyclicalties-ergmTerm | Cyclical ties
cyclicalweights-ergmTerm | Cyclical weights

## -- D --

ddsp-ergmTerm | Directed dyadwise shared partners
degcor-ergmTerm | Degree Correlation
degcrossprod-ergmTerm | Degree Cross-Product
degrange-ergmTerm | Degree range
degree-ergmTerm | Degree
degree1.5-ergmTerm | Degree to the 3/2 power
degreedist | Computes and Returns the Degree Distribution Information for a Given Network
degreedist-ergmConstraint | Preserve the degree distribution of the given network
degreedist.network | Computes and Returns the Degree Distribution Information for a Given Network
degrees-ergmConstraint | Preserve the degree of each vertex of the given network
density-ergmTerm | Density
desp-ergmTerm | Directed edgewise shared partners
deviance.ergm | A 'logLik()' method for 'ergm' fits.
dgwdsp-ergmTerm | Geometrically weighted dyadwise shared partner distribution
dgwesp-ergmTerm | Geometrically weighted edgewise shared partner distribution
dgwnsp-ergmTerm | Geometrically weighted non-edgewise shared partner distribution
diff-ergmTerm | Difference
DiscUnif-ergmReference | Discrete Uniform reference
dnsp-ergmTerm | Directed non-edgewise shared partners
dsp-ergmTerm | Directed dyadwise shared partners
dyadcov-ergmTerm | Dyadic covariate
dyadnoise-ergmConstraint | A soft constraint to adjust the sampled distribution for dyad-level noise with known perturbation probabilities
Dyads-ergmConstraint | Constrain fixed or varying dyad-independent terms

## -- E --

ecoli | Two versions of an E. Coli network dataset
ecoli1 | Two versions of an E. Coli network dataset
ecoli2 | Two versions of an E. Coli network dataset
edgecov-ergmTerm | Edge covariate
edges-ergmConstraint | Preserve the edge count of the given network
edges-ergmTerm | Number of edges in the network
egocentric-ergmConstraint | Preserve values of dyads incident on vertices with given attribute
enformulate.curved | Convert a curved ERGM into a form suitable as initial values for the same ergm. Deprecated in 4.0.0.
enformulate.curved-deprecated | Convert a curved ERGM into a form suitable as initial values for the same ergm. Deprecated in 4.0.0.
enformulate.curved.ergm | Convert a curved ERGM into a form suitable as initial values for the same ergm. Deprecated in 4.0.0.
enformulate.curved.formula | Convert a curved ERGM into a form suitable as initial values for the same ergm. Deprecated in 4.0.0.
equalto-ergmTerm | Number of dyads with values equal to a specific value (within tolerance)
ergm | Exponential-Family Random Graph Models
ergm-constraints | Sample Space Constraints for Exponential-Family Random Graph Models
ergm-hints | MCMC Hints for Exponential-Family Random Graph Models
ergm-keywords | Keywords defined for Exponential-Family Random Graph Models
ergm-options | Global options and term options for the 'ergm' package
ergm-parallel | Parallel Processing in the 'ergm' Package
ergm-proposals | Metropolis-Hastings Proposal Methods for ERGM MCMC
ergm-references | Reference Measures for Exponential-Family Random Graph Models
ergm-terms | Terms used in Exponential Family Random Graph Models
ergm.allstats | Calculate all possible vectors of statistics on a network for an ERGM
ergm.bridge.0.llk | Bridge sampling to evaluate ERGM log-likelihoods and log-likelihood ratios
ergm.bridge.dindstart.llk | Bridge sampling to evaluate ERGM log-likelihoods and log-likelihood ratios
ergm.bridge.llr | Bridge sampling to evaluate ERGM log-likelihoods and log-likelihood ratios
ergm.constraints | Sample Space Constraints for Exponential-Family Random Graph Models
ergm.design | Obtain the set of informative dyads based on the network structure.
ergm.exact | Calculate all possible vectors of statistics on a network for an ERGM
ergm.getCluster | Parallel Processing in the 'ergm' Package
ergm.getnetwork | Acquire and verify the network from the LHS of an 'ergm' formula and verify that it is a valid network.
ergm.godfather | A function to apply a given series of changes to a network.
ergm.godfather.ergm_model | A function to apply a given series of changes to a network.
ergm.godfather.ergm_state | A function to apply a given series of changes to a network.
ergm.godfather.formula | A function to apply a given series of changes to a network.
ergm.hints | MCMC Hints for Exponential-Family Random Graph Models
ergm.keywords | Keywords defined for Exponential-Family Random Graph Models
ergm.object | Exponential-Family Random Graph Models
ergm.parallel | Parallel Processing in the 'ergm' Package
ergm.proposals | Metropolis-Hastings Proposal Methods for ERGM MCMC
ergm.references | Reference Measures for Exponential-Family Random Graph Models
ergm.restartCluster | Parallel Processing in the 'ergm' Package
ergm.stopCluster | Parallel Processing in the 'ergm' Package
ergm.terms | Terms used in Exponential Family Random Graph Models
ergmConstraint | Sample Space Constraints for Exponential-Family Random Graph Models
ergmHint | MCMC Hints for Exponential-Family Random Graph Models
ergmKeyword | Keywords defined for Exponential-Family Random Graph Models
ergmMPLE | ERGM Predictors and response for logistic regression calculation of MPLE
ergmProposal | Metropolis-Hastings Proposal Methods for ERGM MCMC
ergmReference | Reference Measures for Exponential-Family Random Graph Models
ergmTerm | Terms used in Exponential Family Random Graph Models
ergmTerm-options | Global options and term options for the 'ergm' package
ergm_MCMC_sample | Internal Function to Sample Networks and Network Statistics
ergm_MCMC_slave | Internal Function to Sample Networks and Network Statistics
ergm_plot.mcmc.list | Plot MCMC list using 'lattice' package graphics
ergm_state_cache | A rudimentary cache for large objects
ergm_symmetrize | Return a symmetrized version of a binary network
ergm_symmetrize.default | Return a symmetrized version of a binary network
ergm_symmetrize.network | Return a symmetrized version of a binary network
esp-ergmTerm | Directed edgewise shared partners
Exp-ergmTerm | Exponentiate a network's statistic

## -- F --

F-ergmTerm | Filtering on arbitrary one-term model
faux.desert.high | Faux desert High School as a network object
faux.dixon.high | Faux dixon High School as a network object
faux.magnolia.high | Goodreau's Faux Magnolia High School as a network object
faux.mesa.high | Goodreau's Faux Mesa High School as a network object
fauxhigh | Goodreau's Faux Mesa High School as a network object
fix.curved | Convert a curved ERGM into a corresponding "fixed" ERGM.
fix.curved.ergm | Convert a curved ERGM into a corresponding "fixed" ERGM.
fix.curved.formula | Convert a curved ERGM into a corresponding "fixed" ERGM.
fixallbut-ergmConstraint | Preserve the dyad status in all but the given edges
fixedas-ergmConstraint | Fix specific dyads
flobusiness | Florentine Family Marriage and Business Ties Data as a "network" object
flomarriage | Florentine Family Marriage and Business Ties Data as a "network" object
florentine | Florentine Family Marriage and Business Ties Data as a "network" object
For-ergmTerm | A 'for' operator for terms

## -- G --

g4 | Goodreau's four node network as a "network" object
get.MT_terms | Parallel Processing in the 'ergm' Package
geweke.diag.mv | Multivariate version of 'coda"s 'coda::geweke.diag()'.
gof | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
gof.default | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
gof.ergm | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
gof.formula | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
greaterthan-ergmTerm | Number of dyads with values strictly greater than a threshold
gwb1degree-ergmTerm | Geometrically weighted degree distribution for the first mode in a bipartite network
gwb1dsp-ergmTerm | Geometrically weighted dyadwise shared partner distribution for dyads in the first bipartition
gwb2degree-ergmTerm | Geometrically weighted degree distribution for the second mode in a bipartite network
gwb2dsp-ergmTerm | Geometrically weighted dyadwise shared partner distribution for dyads in the second bipartition
gwdegree-ergmTerm | Geometrically weighted degree distribution
gwdsp-ergmTerm | Geometrically weighted dyadwise shared partner distribution
gwesp-ergmTerm | Geometrically weighted edgewise shared partner distribution
gwidegree-ergmTerm | Geometrically weighted in-degree distribution
gwnsp-ergmTerm | Geometrically weighted non-edgewise shared partner distribution
gwodegree-ergmTerm | Geometrically weighted out-degree distribution

## -- H --

hamming-ergmConstraint | Preserve the hamming distance to the given network (BROKEN: Do NOT Use)
hamming-ergmTerm | Hamming distance
hints | MCMC Hints for Exponential-Family Random Graph Models
hints-ergm | MCMC Hints for Exponential-Family Random Graph Models
hints.ergm | MCMC Hints for Exponential-Family Random Graph Models

## -- I --

idegrange-ergmTerm | In-degree range
idegree-ergmTerm | In-degree
idegree1.5-ergmTerm | In-degree to the 3/2 power
idegreedist-ergmConstraint | Preserve the indegree distribution
idegrees-ergmConstraint | Preserve indegree for directed networks
ininterval-ergmTerm | Number of dyads whose values are in an interval
InitErgmConstraint..triadic | Network with strong clustering (triad-closure) effects
InitErgmConstraint.b1degrees | Preserve the actor degree for bipartite networks
InitErgmConstraint.b2degrees | Preserve the receiver degree for bipartite networks
InitErgmConstraint.bd | Constrain maximum and minimum vertex degree
InitErgmConstraint.blockdiag | Block-diagonal structure constraint
InitErgmConstraint.blocks | Constrain blocks of dyads defined by mixing type on a vertex attribute.
InitErgmConstraint.degreedist | Preserve the degree distribution of the given network
InitErgmConstraint.degrees | Preserve the degree of each vertex of the given network
InitErgmConstraint.dyadnoise | A soft constraint to adjust the sampled distribution for dyad-level noise with known perturbation probabilities
InitErgmConstraint.Dyads | Constrain fixed or varying dyad-independent terms
InitErgmConstraint.edges | Preserve the edge count of the given network
InitErgmConstraint.egocentric | Preserve values of dyads incident on vertices with given attribute
InitErgmConstraint.fixallbut | Preserve the dyad status in all but the given edges
InitErgmConstraint.fixedas | Fix specific dyads
InitErgmConstraint.hamming | Preserve the hamming distance to the given network (BROKEN: Do NOT Use)
InitErgmConstraint.idegreedist | Preserve the indegree distribution
InitErgmConstraint.idegrees | Preserve indegree for directed networks
InitErgmConstraint.nodedegrees | Preserve the degree of each vertex of the given network
InitErgmConstraint.observed | Preserve the observed dyads of the given network
InitErgmConstraint.odegreedist | Preserve the outdegree distribution
InitErgmConstraint.odegrees | Preserve outdegree for directed networks
InitErgmConstraint.sparse | Sparse network
InitErgmConstraint.strat | Stratify Proposed Toggles by Mixing Type on a Vertex Attribute
InitErgmConstraint.triadic | Network with strong clustering (triad-closure) effects
InitErgmProposal | Metropolis-Hastings Proposal Methods for ERGM MCMC
InitErgmReference.Bernoulli | Bernoulli reference
InitErgmReference.DiscUnif | Discrete Uniform reference
InitErgmReference.StdNormal | Standard Normal reference
InitErgmReference.Unif | Continuous Uniform reference
InitErgmTerm | Terms used in Exponential Family Random Graph Models
InitErgmTerm.absdiff | Absolute difference in nodal attribute
InitErgmTerm.absdiffcat | Categorical absolute difference in nodal attribute
InitErgmTerm.altkstar | Alternating k-star
InitErgmTerm.asymmetric | Asymmetric dyads
InitErgmTerm.attrcov | Edge covariate by attribute pairing
InitErgmTerm.b1concurrent | Concurrent node count for the first mode in a bipartite network
InitErgmTerm.b1cov | Main effect of a covariate for the first mode in a bipartite network
InitErgmTerm.b1covrange | Range of covariate values for neighbors of a mode-1 node
InitErgmTerm.b1degrange | Degree range for the first mode in a bipartite network
InitErgmTerm.b1degree | Degree for the first mode in a bipartite network
InitErgmTerm.b1dsp | Dyadwise shared partners for dyads in the first bipartition
InitErgmTerm.b1factor | Factor attribute effect for the first mode in a bipartite network
InitErgmTerm.b1factordistinct | Number of distinct neighbor types for the first node
InitErgmTerm.b1mindegree | Minimum degree for the first mode in a bipartite network
InitErgmTerm.b1nodematch | Nodal attribute-based homophily effect for the first mode in a bipartite network
InitErgmTerm.b1sociality | Degree
InitErgmTerm.b1star | k-stars for the first mode in a bipartite network
InitErgmTerm.b1starmix | Mixing matrix for k-stars centered on the first mode of a bipartite network
InitErgmTerm.b1twostar | Two-star census for central nodes centered on the first mode of a bipartite network
InitErgmTerm.b2concurrent | Concurrent node count for the second mode in a bipartite network
InitErgmTerm.b2cov | Main effect of a covariate for the second mode in a bipartite network
InitErgmTerm.b2covrange | Range of covariate values for neighbors of a mode-2 node
InitErgmTerm.b2degrange | Degree range for the second mode in a bipartite network
InitErgmTerm.b2degree | Degree for the second mode in a bipartite network
InitErgmTerm.b2dsp | Dyadwise shared partners for dyads in the second bipartition
InitErgmTerm.b2factor | Factor attribute effect for the second mode in a bipartite network
InitErgmTerm.b2factordistinct | Number of distinct neighbor types for the second mode
InitErgmTerm.b2mindegree | Minimum degree for the second mode in a bipartite network
InitErgmTerm.b2nodematch | Nodal attribute-based homophily effect for the second mode in a bipartite network
InitErgmTerm.b2sociality | Degree
InitErgmTerm.b2star | k-stars for the second mode in a bipartite network
InitErgmTerm.b2starmix | Mixing matrix for k-stars centered on the second mode of a bipartite network
InitErgmTerm.b2twostar | Two-star census for central nodes centered on the second mode of a bipartite network
InitErgmTerm.balance | Balanced triads
InitErgmTerm.coincidence | Coincident node count for the second mode in a bipartite (aka two-mode) network
InitErgmTerm.concurrent | Concurrent node count
InitErgmTerm.concurrentties | Concurrent tie count
InitErgmTerm.ctriad | Cyclic triples
InitErgmTerm.ctriple | Cyclic triples
InitErgmTerm.Curve | Impose a curved structure on term parameters
InitErgmTerm.cycle | k-Cycle Census
InitErgmTerm.cyclicalties | Cyclical ties
InitErgmTerm.ddsp | Directed dyadwise shared partners
InitErgmTerm.degcor | Degree Correlation
InitErgmTerm.degcrossprod | Degree Cross-Product
InitErgmTerm.degrange | Degree range
InitErgmTerm.degree | Degree
InitErgmTerm.degree1.5 | Degree to the 3/2 power
InitErgmTerm.density | Density
InitErgmTerm.desp | Directed edgewise shared partners
InitErgmTerm.dgwdsp | Geometrically weighted dyadwise shared partner distribution
InitErgmTerm.dgwesp | Geometrically weighted edgewise shared partner distribution
InitErgmTerm.dgwnsp | Geometrically weighted non-edgewise shared partner distribution
InitErgmTerm.diff | Difference
InitErgmTerm.dnsp | Directed non-edgewise shared partners
InitErgmTerm.dsp | Directed dyadwise shared partners
InitErgmTerm.dyadcov | Dyadic covariate
InitErgmTerm.edgecov | Edge covariate
InitErgmTerm.edges | Number of edges in the network
InitErgmTerm.esp | Directed edgewise shared partners
InitErgmTerm.Exp | Exponentiate a network's statistic
InitErgmTerm.F | Filtering on arbitrary one-term model
InitErgmTerm.For | A 'for' operator for terms
InitErgmTerm.gwb1degree | Geometrically weighted degree distribution for the first mode in a bipartite network
InitErgmTerm.gwb1dsp | Geometrically weighted dyadwise shared partner distribution for dyads in the first bipartition
InitErgmTerm.gwb2degree | Geometrically weighted degree distribution for the second mode in a bipartite network
InitErgmTerm.gwb2dsp | Geometrically weighted dyadwise shared partner distribution for dyads in the second bipartition
InitErgmTerm.gwdegree | Geometrically weighted degree distribution
InitErgmTerm.gwdsp | Geometrically weighted dyadwise shared partner distribution
InitErgmTerm.gwesp | Geometrically weighted edgewise shared partner distribution
InitErgmTerm.gwidegree | Geometrically weighted in-degree distribution
InitErgmTerm.gwnsp | Geometrically weighted non-edgewise shared partner distribution
InitErgmTerm.gwodegree | Geometrically weighted out-degree distribution
InitErgmTerm.hamming | Hamming distance
InitErgmTerm.idegrange | In-degree range
InitErgmTerm.idegree | In-degree
InitErgmTerm.idegree1.5 | In-degree to the 3/2 power
InitErgmTerm.intransitive | Intransitive triads
InitErgmTerm.isolatededges | Isolated edges
InitErgmTerm.isolates | Isolates
InitErgmTerm.istar | In-stars
InitErgmTerm.kstar | k-stars
InitErgmTerm.Label | Modify terms' coefficient names
InitErgmTerm.localtriangle | Triangles within neighborhoods
InitErgmTerm.Log | Take a natural logarithm of a network's statistic
InitErgmTerm.m2star | Mixed 2-stars, a.k.a 2-paths
InitErgmTerm.meandeg | Mean vertex degree
InitErgmTerm.mm | Mixing matrix cells and margins
InitErgmTerm.mutual | Mutuality
InitErgmTerm.nearsimmelian | Near simmelian triads
InitErgmTerm.nodecov | Main effect of a covariate
InitErgmTerm.nodecovrange | Range of covariate values for neighbors of a node
InitErgmTerm.nodefactor | Factor attribute effect
InitErgmTerm.nodefactordistinct | Number of distinct neighbor types
InitErgmTerm.nodeicov | Main effect of a covariate for in-edges
InitErgmTerm.nodeicovrange | Range of covariate values for in-neighbors of a node
InitErgmTerm.nodeifactor | Factor attribute effect for in-edges
InitErgmTerm.nodeifactordistinct | Number of distinct in-neighbor types
InitErgmTerm.nodemain | Main effect of a covariate
InitErgmTerm.nodematch | Uniform homophily and differential homophily
InitErgmTerm.NodematchFilter | Filtering on nodematch
InitErgmTerm.nodemix | Nodal attribute mixing
InitErgmTerm.nodeocov | Main effect of a covariate for out-edges
InitErgmTerm.nodeocovrange | Range of covariate values for out-neighbors of a node
InitErgmTerm.nodeofactor | Factor attribute effect for out-edges
InitErgmTerm.nodeofactordistinct | Number of distinct out-neighbor types
InitErgmTerm.nsp | Directed non-edgewise shared partners
InitErgmTerm.odegrange | Out-degree range
InitErgmTerm.odegree | Out-degree
InitErgmTerm.odegree1.5 | Out-degree to the 3/2 power
InitErgmTerm.Offset | Terms with fixed coefficients
InitErgmTerm.opentriad | Open triads
InitErgmTerm.ostar | k-Outstars
InitErgmTerm.Parametrise | Impose a curved structure on term parameters
InitErgmTerm.Parametrize | Impose a curved structure on term parameters
InitErgmTerm.Prod | A product (or an arbitrary power combination) of one or more formulas
InitErgmTerm.Proj1 | Evaluation on a projection of a bipartite network
InitErgmTerm.Proj2 | Evaluation on a projection of a bipartite network
InitErgmTerm.Project | Evaluation on a projection of a bipartite network
InitErgmTerm.receiver | Receiver effect
InitErgmTerm.S | Evaluation on an induced subgraph
InitErgmTerm.sender | Sender effect
InitErgmTerm.simmelian | Simmelian triads
InitErgmTerm.simmelianties | Ties in simmelian triads
InitErgmTerm.smalldiff | Number of ties between actors with similar attribute values
InitErgmTerm.sociality | Undirected degree
InitErgmTerm.Sum | A sum (or an arbitrary linear combination) of one or more formulas
InitErgmTerm.Symmetrize | Evaluation on symmetrized (undirected) network
InitErgmTerm.threepath | Three-trails
InitErgmTerm.threetrail | Three-trails
InitErgmTerm.transitive | Transitive triads
InitErgmTerm.transitiveties | Transitive ties
InitErgmTerm.triadcensus | Triad census
InitErgmTerm.triangle | Triangles
InitErgmTerm.tripercent | Triangle percentage
InitErgmTerm.ttriad | Transitive triples
InitErgmTerm.ttriple | Transitive triples
InitErgmTerm.twopath | 2-Paths
InitErgmWtTerm | Terms used in Exponential Family Random Graph Models
InitWtErgmProposal | Metropolis-Hastings Proposal Methods for ERGM MCMC
InitWtErgmTerm.absdiff | Absolute difference in nodal attribute
InitWtErgmTerm.absdiffcat | Categorical absolute difference in nodal attribute
InitWtErgmTerm.atleast | Number of dyads with values greater than or equal to a threshold
InitWtErgmTerm.atmost | Number of dyads with values less than or equal to a threshold
InitWtErgmTerm.B | Wrap binary terms for use in valued models
InitWtErgmTerm.b1cov | Main effect of a covariate for the first mode in a bipartite network
InitWtErgmTerm.b1factor | Factor attribute effect for the first mode in a bipartite network
InitWtErgmTerm.b1sociality | Degree
InitWtErgmTerm.b2cov | Main effect of a covariate for the second mode in a bipartite network
InitWtErgmTerm.b2factor | Factor attribute effect for the second mode in a bipartite network
InitWtErgmTerm.b2sociality | Degree
InitWtErgmTerm.Curve | Impose a curved structure on term parameters
InitWtErgmTerm.cyclicalties | Cyclical ties
InitWtErgmTerm.cyclicalweights | Cyclical weights
InitWtErgmTerm.diff | Difference
InitWtErgmTerm.edgecov | Edge covariate
InitWtErgmTerm.edges | Number of edges in the network
InitWtErgmTerm.equalto | Number of dyads with values equal to a specific value (within tolerance)
InitWtErgmTerm.Exp | Exponentiate a network's statistic
InitWtErgmTerm.greaterthan | Number of dyads with values strictly greater than a threshold
InitWtErgmTerm.ininterval | Number of dyads whose values are in an interval
InitWtErgmTerm.Label | Modify terms' coefficient names
InitWtErgmTerm.Log | Take a natural logarithm of a network's statistic
InitWtErgmTerm.match | Uniform homophily and differential homophily
InitWtErgmTerm.mm | Mixing matrix cells and margins
InitWtErgmTerm.mutual | Mutuality
InitWtErgmTerm.nodecov | Main effect of a covariate
InitWtErgmTerm.nodecovar | Covariance of undirected dyad values incident on each actor
InitWtErgmTerm.nodefactor | Factor attribute effect
InitWtErgmTerm.nodeicov | Main effect of a covariate for in-edges
InitWtErgmTerm.nodeicovar | Covariance of in-dyad values incident on each actor
InitWtErgmTerm.nodeifactor | Factor attribute effect for in-edges
InitWtErgmTerm.nodemain | Main effect of a covariate
InitWtErgmTerm.nodematch | Uniform homophily and differential homophily
InitWtErgmTerm.nodemix | Nodal attribute mixing
InitWtErgmTerm.nodeocov | Main effect of a covariate for out-edges
InitWtErgmTerm.nodeocovar | Covariance of out-dyad values incident on each actor
InitWtErgmTerm.nodeofactor | Factor attribute effect for out-edges
InitWtErgmTerm.nonzero | Number of edges in the network
InitWtErgmTerm.Parametrise | Impose a curved structure on term parameters
InitWtErgmTerm.Parametrize | Impose a curved structure on term parameters
InitWtErgmTerm.Prod | A product (or an arbitrary power combination) of one or more formulas
InitWtErgmTerm.receiver | Receiver effect
InitWtErgmTerm.sender | Sender effect
InitWtErgmTerm.smallerthan | Number of dyads with values strictly smaller than a threshold
InitWtErgmTerm.sociality | Undirected degree
InitWtErgmTerm.Sum | A sum (or an arbitrary linear combination) of one or more formulas
InitWtErgmTerm.sum | Sum of dyad values (optionally taken to a power)
InitWtErgmTerm.transitiveweights | Transitive weights
intransitive-ergmTerm | Intransitive triads
is.curved | Testing for curved exponential family
is.curved.ergm | Testing for curved exponential family
is.curved.formula | Testing for curved exponential family
is.curved.NULL | Testing for curved exponential family
is.dyad.independent | Testing for dyad-independence
is.dyad.independent.ergm | Testing for dyad-independence
is.dyad.independent.ergm_conlist | Testing for dyad-independence
is.dyad.independent.formula | Testing for dyad-independence
is.dyad.independent.NULL | Testing for dyad-independence
is.ergm | Exponential-Family Random Graph Models
is.na.ergm | Exponential-Family Random Graph Models
is.valued | Function to check whether an ERGM fit or some aspect of it is valued
is.valued.edgelist | Function to check whether an ERGM fit or some aspect of it is valued
is.valued.ergm | Function to check whether an ERGM fit or some aspect of it is valued
is.valued.ergm_state | Function to check whether an ERGM fit or some aspect of it is valued
is.valued.network | Function to check whether an ERGM fit or some aspect of it is valued
isolatededges-ergmTerm | Isolated edges
isolates-ergmTerm | Isolates
istar-ergmTerm | In-stars

## -- K --

kapferer | Kapferer's tailor shop data
kapferer2 | Kapferer's tailor shop data
keywords-ergm | Keywords defined for Exponential-Family Random Graph Models
keywords.ergm | Keywords defined for Exponential-Family Random Graph Models
kstar-ergmTerm | k-stars

## -- L --

Label-ergmTerm | Modify terms' coefficient names
LARGEST | Specifying nodal attributes and their levels
localtriangle-ergmTerm | Triangles within neighborhoods
Log-ergmTerm | Take a natural logarithm of a network's statistic
logLik.ergm | A 'logLik()' method for 'ergm' fits.
logLikNull | Calculate the null model likelihood
logLikNull.ergm | Calculate the null model likelihood

## -- M --

m2star-ergmTerm | Mixed 2-stars, a.k.a 2-paths
match-ergmTerm | Uniform homophily and differential homophily
mcmc.diagnostics | Conduct MCMC diagnostics on a model fit
mcmc.diagnostics.default | Conduct MCMC diagnostics on a model fit
mcmc.diagnostics.ergm | Conduct MCMC diagnostics on a model fit
meandeg-ergmTerm | Mean vertex degree
mm-ergmTerm | Mixing matrix cells and margins
molecule | Synthetic network with 20 nodes and 28 edges
mutual-ergmTerm | Mutuality

## -- N --

nearsimmelian-ergmTerm | Near simmelian triads
network.list | A convenience container for a list of 'network' objects, output by 'simulate.ergm()' among others.
nobs.ergm | Exponential-Family Random Graph Models
nodal.attr | Specifying nodal attributes and their levels
nodal.attribute | Specifying nodal attributes and their levels
nodal_attributes | Specifying nodal attributes and their levels
node.attr | Specifying nodal attributes and their levels
node.attribute | Specifying nodal attributes and their levels
nodecov-ergmTerm | Main effect of a covariate
nodecovar-ergmTerm | Covariance of undirected dyad values incident on each actor
nodecovrange-ergmTerm | Range of covariate values for neighbors of a node
nodedegrees-ergmConstraint | Preserve the degree of each vertex of the given network
nodefactor-ergmTerm | Factor attribute effect
nodefactordistinct-ergmTerm | Number of distinct neighbor types
nodeicov-ergmTerm | Main effect of a covariate for in-edges
nodeicovar-ergmTerm | Covariance of in-dyad values incident on each actor
nodeicovrange-ergmTerm | Range of covariate values for in-neighbors of a node
nodeifactor-ergmTerm | Factor attribute effect for in-edges
nodeifactordistinct-ergmTerm | Number of distinct in-neighbor types
nodeisqrtcovar-ergmTerm | Covariance of in-dyad values incident on each actor
nodemain-ergmTerm | Main effect of a covariate
nodematch-ergmTerm | Uniform homophily and differential homophily
NodematchFilter-ergmTerm | Filtering on nodematch
nodemix-ergmTerm | Nodal attribute mixing
nodeocov-ergmTerm | Main effect of a covariate for out-edges
nodeocovar-ergmTerm | Covariance of out-dyad values incident on each actor
nodeocovrange-ergmTerm | Range of covariate values for out-neighbors of a node
nodeofactor-ergmTerm | Factor attribute effect for out-edges
nodeofactordistinct-ergmTerm | Number of distinct out-neighbor types
nodesqrtcovar-ergmTerm | Covariance of undirected dyad values incident on each actor
nonzero-ergmTerm | Number of edges in the network
nparam | Length of the parameter vector associated with an object or with its terms.
nparam.default | Length of the parameter vector associated with an object or with its terms.
nparam.ergm | Length of the parameter vector associated with an object or with its terms.
nsp-ergmTerm | Directed non-edgewise shared partners
nthreads | Parallel Processing in the 'ergm' Package
nthreads.cluster | Parallel Processing in the 'ergm' Package
nthreads.control.list | Parallel Processing in the 'ergm' Package
nthreads.NULL | Parallel Processing in the 'ergm' Package

## -- O --

observed-ergmConstraint | Preserve the observed dyads of the given network
odegrange-ergmTerm | Out-degree range
odegree-ergmTerm | Out-degree
odegree1.5-ergmTerm | Out-degree to the 3/2 power
odegreedist-ergmConstraint | Preserve the outdegree distribution
odegrees-ergmConstraint | Preserve outdegree for directed networks
Offset-ergmTerm | Terms with fixed coefficients
on | Specifying nodal attributes and their levels
opentriad-ergmTerm | Open triads
ostar-ergmTerm | k-Outstars

## -- P --

parallel | Parallel Processing in the 'ergm' Package
parallel-ergm | Parallel Processing in the 'ergm' Package
parallel.ergm | Parallel Processing in the 'ergm' Package
Parametrise-ergmTerm | Impose a curved structure on term parameters
Parametrize-ergmTerm | Impose a curved structure on term parameters
param_names | Names of the parameters associated with an object.
param_names.default | Names of the parameters associated with an object.
param_names<- | Names of the parameters associated with an object.
plot.gof | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
predict.ergm | ERGM-based tie probabilities
predict.formula | ERGM-based tie probabilities
print.ergm | Exponential-Family Random Graph Models
print.gof | Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model
print.network.list | A convenience container for a list of 'network' objects, output by 'simulate.ergm()' among others.
print.summary.ergm | Summarizing ERGM Model Fits
Prod-ergmTerm | A product (or an arbitrary power combination) of one or more formulas
Proj1-ergmTerm | Evaluation on a projection of a bipartite network
Proj2-ergmTerm | Evaluation on a projection of a bipartite network
Project-ergmTerm | Evaluation on a projection of a bipartite network
proposals-ergm | Metropolis-Hastings Proposal Methods for ERGM MCMC
proposals.ergm | Metropolis-Hastings Proposal Methods for ERGM MCMC

## -- R --

rank_test.ergm | A lack-of-fit test for ERGMs
receiver-ergmTerm | Receiver effect
references-ergm | Reference Measures for Exponential-Family Random Graph Models
references.ergm | Reference Measures for Exponential-Family Random Graph Models

## -- S --

S-ergmTerm | Evaluation on an induced subgraph
samplike | Cumulative network of positive affection within a monastery as a "network" object
samplk | Longitudinal networks of positive affection within a monastery as a "network" object
samplk1 | Longitudinal networks of positive affection within a monastery as a "network" object
samplk2 | Longitudinal networks of positive affection within a monastery as a "network" object
samplk3 | Longitudinal networks of positive affection within a monastery as a "network" object
sampson | Cumulative network of positive affection within a monastery as a "network" object
san | Generate networks with a given set of network statistics
san.default | Generate networks with a given set of network statistics
san.ergm_model | Generate networks with a given set of network statistics
san.formula | Generate networks with a given set of network statistics
search.ergmConstraints | Search ERGM terms, constraints, references, hints, and proposals
search.ergmHints | Search ERGM terms, constraints, references, hints, and proposals
search.ergmProposals | Search ERGM terms, constraints, references, hints, and proposals
search.ergmReferences | Search ERGM terms, constraints, references, hints, and proposals
search.ergmTerms | Search ERGM terms, constraints, references, hints, and proposals
sender-ergmTerm | Sender effect
set.MT_terms | Parallel Processing in the 'ergm' Package
simmelian-ergmTerm | Simmelian triads
simmelianties-ergmTerm | Ties in simmelian triads
simulate.ergm | Draw from the distribution of an Exponential Family Random Graph Model
simulate.ergm_model | Draw from the distribution of an Exponential Family Random Graph Model
simulate.ergm_state | Draw from the distribution of an Exponential Family Random Graph Model
simulate.ergm_state_full | Draw from the distribution of an Exponential Family Random Graph Model
simulate.formula | A 'simulate' Method for 'formula' objects that dispatches based on the Left-Hand Side
simulate.formula.ergm | Draw from the distribution of an Exponential Family Random Graph Model
simulate.formula_lhs | A 'simulate' Method for 'formula' objects that dispatches based on the Left-Hand Side
simulate.formula_lhs_network | Draw from the distribution of an Exponential Family Random Graph Model
simulate_formula | Draw from the distribution of an Exponential Family Random Graph Model
simulate_formula.ergm_state | Draw from the distribution of an Exponential Family Random Graph Model
simulate_formula.network | Draw from the distribution of an Exponential Family Random Graph Model
smalldiff-ergmTerm | Number of ties between actors with similar attribute values
smallerthan-ergmTerm | Number of dyads with values strictly smaller than a threshold
SMALLEST | Specifying nodal attributes and their levels
snctrl | Statnet Control
sociality-ergmTerm | Undirected degree
sparse-ergmConstraint | Sparse network
sparse-ergmHint | Sparse network
spectrum0.mvar | Multivariate version of 'coda"s 'spectrum0.ar()'.
StdNormal-ergmReference | Standard Normal reference
strat-ergmConstraint | Stratify Proposed Toggles by Mixing Type on a Vertex Attribute
strat-ergmHint | Stratify Proposed Toggles by Mixing Type on a Vertex Attribute
Sum-ergmTerm | A sum (or an arbitrary linear combination) of one or more formulas
sum-ergmTerm | Sum of dyad values (optionally taken to a power)
summary | Calculation of network or graph statistics or other attributes specified on a formula
summary.ergm | Summarizing ERGM Model Fits
summary.formula | Calculation of network or graph statistics or other attributes specified on a formula
summary.network.list | A convenience container for a list of 'network' objects, output by 'simulate.ergm()' among others.
Symmetrize-ergmTerm | Evaluation on symmetrized (undirected) network

## -- T --

tailor | Kapferer's tailor shop data
term.options | Global options and term options for the 'ergm' package
terms-ergm | Terms used in Exponential Family Random Graph Models
terms.ergm | Terms used in Exponential Family Random Graph Models
threepath-ergmTerm | Three-trails
threetrail-ergmTerm | Three-trails
transitive-ergmTerm | Transitive triads
transitiveties-ergmTerm | Transitive ties
transitiveweights-ergmTerm | Transitive weights
triadcensus-ergmTerm | Triad census
triadic-ergmConstraint | Network with strong clustering (triad-closure) effects
triadic-ergmHint | Network with strong clustering (triad-closure) effects
triangle-ergmTerm | Triangles
triangles-ergmTerm | Triangles
tripercent-ergmTerm | Triangle percentage
ttriad-ergmTerm | Transitive triples
ttriple-ergmTerm | Transitive triples
twopath-ergmTerm | 2-Paths

## -- U --

Unif-ergmReference | Continuous Uniform reference
update.network | Update the edges in a network based on a matrix
update_network | Update the edges in a network based on a matrix
update_network.data.frame | Update the edges in a network based on a matrix
update_network.ergm_state | Update the edges in a network based on a matrix
update_network.matrix | Update the edges in a network based on a matrix
update_network.matrix_edgelist | Update the edges in a network based on a matrix

## -- V --

vcov.ergm | Exponential-Family Random Graph Models
vertex.attr | Specifying nodal attributes and their levels
vertex.attribute | Specifying nodal attributes and their levels

## -- W --

wtd.median | Weighted Median

## -- misc --

.dyads-ergmConstraint | A meta-constraint indicating handling of arbitrary dyadic constraints
.simulate_formula.network | Draw from the distribution of an Exponential Family Random Graph Model
.triadic-ergmHint | Network with strong clustering (triad-closure) effects