This package is considered a duplicate. The official version of this package is found at:https://statnet.r-universe.dev/ergm
Package: ergm 4.7.5
Pavel N. Krivitsky
ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks
An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i03> and Krivitsky, Hunter, Morris, and Klumb (2023) <doi:10.18637/jss.v105.i06>.
Authors:
ergm_4.7.5.tar.gz
ergm_4.7.5.tar.gz(r-4.5-noble)ergm_4.7.5.tar.gz(r-4.4-noble)
ergm_4.7.5.tgz(r-4.4-emscripten)ergm_4.7.5.tgz(r-4.3-emscripten)
ergm.pdf |ergm.html✨
ergm/json (API)
NEWS
| # Install 'ergm' in R: |
| install.packages('ergm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/statnet/ergm/issues
Datasets:
- 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
- ecoli1 - Two versions of an E. Coli network dataset
- ecoli2 - Two versions of an E. Coli network dataset
- 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
- flobusiness - Florentine Family Marriage and Business Ties Data as a "network" object
- flomarriage - Florentine Family Marriage and Business Ties Data as a "network" object
- g4 - Goodreau's four node network as a "network" object
- kapferer - Kapferer's tailor shop data
- kapferer2 - Kapferer's tailor shop data
- molecule - Synthetic network with 20 nodes and 28 edges
- samplike - Cumulative network 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
Last updated 18 days agofrom:fe6641aa5e. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 07 2024 |
| R-4.5-linux-x86_64 | OK | Nov 07 2024 |
Exports:.simulate_formula.network%ergmlhs%%ergmlhs%<-approx.hotelling.diff.testas.ergm_modelas.rlebdmcall.ErgmTermcheck.ErgmTermCOLLAPSE_SMALLESTcontrol.ergmcontrol.ergm.bridgecontrol.ergm.godfathercontrol.gof.ergmcontrol.gof.formulacontrol.logLik.ergmcontrol.sancontrol.simulatecontrol.simulate.ergmcontrol.simulate.formulacontrol.simulate.formula.ergmconvert_ergmlhsdegreedistenformulate.curvedergmergm_attr_levelsergm_bd_initergm_Cstate_clearergm_cutoff_messageergm_dyadgen_selectergm_edgecov_argsergm_get_vattrERGM_GET_VATTR_MULTIPLE_TYPESergm_GWDECAYergm_Init_abortergm_Init_informergm_Init_messageergm_Init_stopergm_Init_tryergm_Init_warnergm_Init_warningergm_keywordERGM_LEVELS_SPECergm_MCMC_sampleergm_MCMC_slaveergm_mk_std_op_namewrapergm_modelergm_no_ext.encodeergm_plot.mcmc.listergm_preprocess_responseergm_propagate_ext.encodeergm_proposalergm_proposal_tableergm_SAN_slaveergm_stateERGM_STATE_C_CHANGEDergm_state_cacheERGM_STATE_R_CHANGEDergm_state_receiveERGM_STATE_RECONCILEDergm_state_sendergm_symmetrizeERGM_VATTR_SPECERGM_VATTR_SPEC_NULLergm.allstatsergm.bridge.0.llkergm.bridge.dindstart.llkergm.bridge.llrergm.designergm.estfunergm.etaergm.etagradergm.etagradmultergm.exactergm.geodistdistergm.geodistnergm.getClusterergm.getnetworkergm.godfatherergm.plergm.restartClusterergm.stopClusterergmMPLEfix.curvedget.MT_termsget.node.attrgeweke.diag.mvgofis.curvedis.dyad.independentis.ergmis.ergm_stateis.valuedLARGESTlogLikNullmcmc.diagnosticsnetwork.listnparamnthreadsnvattr.copy.networkoffset.info.formulaparam_namesparam_names<-rank_test.ergmrlebdmsansearch.ergmConstraintssearch.ergmHintssearch.ergmProposalssearch.ergmReferencessearch.ergmTermsset.MT_termsshrink_into_CHsimulate_formulaSMALLESTsnctrlspectrum0.mvarsummary_formulato_ergm_Cdoubleupdate_networkwrap.ergm_modelwtd.median
Dependencies:cachemclicodaDEoptimRevaluatefansifastmapgluehighrknitrlatticelifecyclelpSolveAPImagrittrMatrixmemoisenetworkpillarpkgconfigpurrrrbibutilsRdpackrlangrlerobustbasestatnet.commonstringistringrtibbletrustutf8vctrsxfunyaml
API for Callback Functions for Network and WtNetwork Structures
Rendered fromNetwork-Callback-API.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2024-11-06
Started: 2021-06-14
API for ergm Terms
Rendered fromTerms-API.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2024-11-06
Started: 2021-06-14
API for MCMC Proposal Selection
Rendered fromProposal-Lookup-API.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2024-11-06
Started: 2021-06-14
ERGM terms cross-reference
Rendered fromergm-term-crossRef.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2022-06-01
Started: 2014-12-09
Introduction to Exponential-family Random Graph Models with ergm
Rendered fromergm.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2024-11-06
Started: 2021-06-14
Nodal Attribute Specification in ERGM Terms
Rendered fromnodal_attributes.Rmdusingknitr::rmarkdownon Nov 07 2024.Last update: 2024-10-08
Started: 2020-10-14
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A meta-constraint indicating handling of arbitrary dyadic constraints | .dyads-ergmConstraint |
| Absolute difference in nodal attribute | absdiff-ergmTerm InitErgmTerm.absdiff InitWtErgmTerm.absdiff |
| Categorical absolute difference in nodal attribute | absdiffcat-ergmTerm InitErgmTerm.absdiffcat InitWtErgmTerm.absdiffcat |
| Alternating k-star | altkstar-ergmTerm InitErgmTerm.altkstar |
| ANOVA for ERGM Fits | anova.ergm anova.ergmlist |
| Approximate Hotelling T^2-Test for One or Two Population Means | approx.hotelling.diff.test |
| Create a Simple Random network of a Given Size | as.network.numeric |
| Asymmetric dyads | asymmetric-ergmTerm InitErgmTerm.asymmetric |
| Number of dyads with values greater than or equal to a threshold | atleast-ergmTerm InitWtErgmTerm.atleast |
| Number of dyads with values less than or equal to a threshold | atmost-ergmTerm InitWtErgmTerm.atmost |
| Edge covariate by attribute pairing | attrcov-ergmTerm InitErgmTerm.attrcov |
| Wrap binary terms for use in valued models | B-ergmTerm InitWtErgmTerm.B |
| Concurrent node count for the first mode in a bipartite network | b1concurrent-ergmTerm InitErgmTerm.b1concurrent |
| Main effect of a covariate for the first mode in a bipartite network | b1cov-ergmTerm InitErgmTerm.b1cov InitWtErgmTerm.b1cov |
| Degree range for the first mode in a bipartite network | b1degrange-ergmTerm InitErgmTerm.b1degrange |
| Degree for the first mode in a bipartite network | b1degree-ergmTerm InitErgmTerm.b1degree |
| Preserve the actor degree for bipartite networks | b1degrees-ergmConstraint InitErgmConstraint.b1degrees |
| Dyadwise shared partners for dyads in the first bipartition | b1dsp-ergmTerm InitErgmTerm.b1dsp |
| Factor attribute effect for the first mode in a bipartite network | b1factor-ergmTerm InitErgmTerm.b1factor InitWtErgmTerm.b1factor |
| Minimum degree for the first mode in a bipartite network | b1mindegree-ergmTerm InitErgmTerm.b1mindegree |
| Nodal attribute-based homophily effect for the first mode in a bipartite network | b1nodematch-ergmTerm InitErgmTerm.b1nodematch |
| Degree | b1sociality-ergmTerm InitErgmTerm.b1sociality InitWtErgmTerm.b1sociality |
| k-stars for the first mode in a bipartite network | b1star-ergmTerm InitErgmTerm.b1star |
| Mixing matrix for k-stars centered on the first mode of a bipartite network | b1starmix-ergmTerm InitErgmTerm.b1starmix |
| Two-star census for central nodes centered on the first mode of a bipartite network | b1twostar-ergmTerm InitErgmTerm.b1twostar |
| Concurrent node count for the second mode in a bipartite network | b2concurrent-ergmTerm InitErgmTerm.b2concurrent |
| Main effect of a covariate for the second mode in a bipartite network | b2cov-ergmTerm InitErgmTerm.b2cov InitWtErgmTerm.b2cov |
| Degree range for the second mode in a bipartite network | b2degrange-ergmTerm InitErgmTerm.b2degrange |
| Degree for the second mode in a bipartite network | b2degree-ergmTerm InitErgmTerm.b2degree |
| Preserve the receiver degree for bipartite networks | b2degrees-ergmConstraint InitErgmConstraint.b2degrees |
| Dyadwise shared partners for dyads in the second bipartition | b2dsp-ergmTerm InitErgmTerm.b2dsp |
| Factor attribute effect for the second mode in a bipartite network | b2factor-ergmTerm InitErgmTerm.b2factor InitWtErgmTerm.b2factor |
| Minimum degree for the second mode in a bipartite network | b2mindegree-ergmTerm InitErgmTerm.b2mindegree |
| Nodal attribute-based homophily effect for the second mode in a bipartite network | b2nodematch-ergmTerm InitErgmTerm.b2nodematch |
| Degree | b2sociality-ergmTerm InitErgmTerm.b2sociality InitWtErgmTerm.b2sociality |
| k-stars for the second mode in a bipartite network | b2star-ergmTerm InitErgmTerm.b2star |
| Mixing matrix for k-stars centered on the second mode of a bipartite network | b2starmix-ergmTerm InitErgmTerm.b2starmix |
| Two-star census for central nodes centered on the second mode of a bipartite network | b2twostar-ergmTerm InitErgmTerm.b2twostar |
| Balanced triads | balance-ergmTerm InitErgmTerm.balance |
| Constrain maximum and minimum vertex degree | bd-ergmConstraint InitErgmConstraint.bd |
| Bernoulli reference | Bernoulli-ergmReference InitErgmReference.Bernoulli |
| Block-diagonal structure constraint | blockdiag-ergmConstraint InitErgmConstraint.blockdiag |
| Constrain blocks of dyads defined by mixing type on a vertex attribute. | blocks-ergmConstraint InitErgmConstraint.blocks |
| Ensures an Ergm Term and its Arguments Meet Appropriate Conditions | check.ErgmTerm |
| Target statistics and model fit to a hypothetical 50,000-node network population with 50,000 nodes based on egocent | cohab cohab_MixMat cohab_PopWts cohab_TargetStats |
| Coincident node count for the second mode in a bipartite (aka two-mode) network | coincidence-ergmTerm InitErgmTerm.coincidence |
| Concurrent node count | concurrent-ergmTerm InitErgmTerm.concurrent |
| Concurrent tie count | concurrentties-ergmTerm InitErgmTerm.concurrentties |
| Auxiliary function for fine-tuning ERGM fitting. | control.ergm |
| Auxiliaries for Controlling 'ergm.bridge.llr()' and 'logLik.ergm()' | control.ergm.bridge control.logLik.ergm |
| Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation | control.gof control.gof.ergm control.gof.formula |
| Auxiliary for Controlling SAN | control.san |
| Auxiliary for Controlling ERGM Simulation | control.simulate control.simulate.ergm control.simulate.formula control.simulate.formula.ergm |
| Cyclic triples | ctriad-ergmTerm ctriple-ergmTerm InitErgmTerm.ctriad InitErgmTerm.ctriple |
| Impose a curved structure on term parameters | Curve-ergmTerm InitErgmTerm.Curve InitErgmTerm.Parametrise InitErgmTerm.Parametrize InitWtErgmTerm.Curve InitWtErgmTerm.Parametrise InitWtErgmTerm.Parametrize Parametrise-ergmTerm Parametrize-ergmTerm |
| k-Cycle Census | cycle-ergmTerm InitErgmTerm.cycle |
| Cyclical ties | cyclicalties-ergmTerm InitErgmTerm.cyclicalties InitWtErgmTerm.cyclicalties |
| Cyclical weights | cyclicalweights-ergmTerm InitWtErgmTerm.cyclicalweights |
| Degree Correlation | degcor-ergmTerm InitErgmTerm.degcor |
| Degree Cross-Product | degcrossprod-ergmTerm InitErgmTerm.degcrossprod |
| Degree range | degrange-ergmTerm InitErgmTerm.degrange |
| Degree | degree-ergmTerm InitErgmTerm.degree |
| Degree to the 3/2 power | degree1.5-ergmTerm InitErgmTerm.degree1.5 |
| Computes and Returns the Degree Distribution Information for a Given Network | degreedist degreedist.network |
| Preserve the degree distribution of the given network | degreedist-ergmConstraint InitErgmConstraint.degreedist |
| Preserve the degree of each vertex of the given network | degrees-ergmConstraint InitErgmConstraint.degrees InitErgmConstraint.nodedegrees nodedegrees-ergmConstraint |
| Density | density-ergmTerm InitErgmTerm.density |
| Difference | diff-ergmTerm InitErgmTerm.diff InitWtErgmTerm.diff |
| Discrete Uniform reference | DiscUnif-ergmReference InitErgmReference.DiscUnif |
| Directed dyadwise shared partners | ddsp-ergmTerm dsp-ergmTerm InitErgmTerm.ddsp InitErgmTerm.dsp |
| Dyadic covariate | dyadcov-ergmTerm InitErgmTerm.dyadcov |
| A soft constraint to adjust the sampled distribution for dyad-level noise with known perturbation probabilities | dyadnoise-ergmConstraint InitErgmConstraint.dyadnoise |
| Constrain fixed or varying dyad-independent terms | Dyads-ergmConstraint InitErgmConstraint.Dyads |
| Two versions of an E. Coli network dataset | ecoli ecoli1 ecoli2 |
| Edge covariate | edgecov-ergmTerm InitErgmTerm.edgecov InitWtErgmTerm.edgecov |
| Preserve the edge count of the given network | edges-ergmConstraint InitErgmConstraint.edges |
| Number of edges in the network | edges-ergmTerm InitErgmTerm.edges InitWtErgmTerm.edges InitWtErgmTerm.nonzero nonzero-ergmTerm |
| Preserve values of dyads incident on vertices with given attribute | egocentric-ergmConstraint InitErgmConstraint.egocentric |
| Convert a curved ERGM into a form suitable as initial values for the same ergm. Deprecated in 4.0.0. | enformulate.curved enformulate.curved-deprecated enformulate.curved.ergm enformulate.curved.formula |
| Number of dyads with values equal to a specific value (within tolerance) | equalto-ergmTerm InitWtErgmTerm.equalto |
| Exponential-Family Random Graph Models | anyNA.ergm ergm ergm.object is.ergm is.na.ergm nobs.ergm print.ergm vcov.ergm |
| Internal Function to Sample Networks and Network Statistics | ergm_MCMC_sample ergm_MCMC_slave |
| Plot MCMC list using 'lattice' package graphics | ergm_plot.mcmc.list |
| A rudimentary cache for large objects | ergm_state_cache |
| Return a symmetrized version of a binary network | ergm_symmetrize ergm_symmetrize.default ergm_symmetrize.network |
| Global options and term options for the 'ergm' package | ergm-options ergmTerm-options term.options |
| Parallel Processing in the 'ergm' Package | ergm-parallel ergm.getCluster ergm.parallel ergm.restartCluster ergm.stopCluster get.MT_terms nthreads nthreads.cluster nthreads.control.list nthreads.NULL parallel parallel-ergm parallel.ergm set.MT_terms |
| Calculate all possible vectors of statistics on a network for an ERGM | ergm.allstats ergm.exact |
| Bridge sampling to evaluate ERGM log-likelihoods and log-likelihood ratios | ergm.bridge.0.llk ergm.bridge.dindstart.llk ergm.bridge.llr |
| Obtain the set of informative dyads based on the network structure. | ergm.design |
| Acquire and verify the network from the LHS of an 'ergm' formula and verify that it is a valid network. | ergm.getnetwork |
| A function to apply a given series of changes to a network. | ergm.godfather ergm.godfather.ergm_model ergm.godfather.ergm_state ergm.godfather.formula |
| Sample Space Constraints for Exponential-Family Random Graph Models | constraints-ergm constraints.ergm ergm-constraints ergm.constraints ergmConstraint |
| MCMC Hints for Exponential-Family Random Graph Models | ergm-hints ergm.hints ergmHint hints hints-ergm hints.ergm |
| Keywords defined for Exponential-Family Random Graph Models | ergm-keywords ergm.keywords ergmKeyword keywords-ergm keywords.ergm |
| ERGM Predictors and response for logistic regression calculation of MPLE | ergmMPLE |
| Metropolis-Hastings Proposal Methods for ERGM MCMC | ergm-proposals ergm.proposals ergmProposal InitErgmProposal InitWtErgmProposal proposals-ergm proposals.ergm |
| Reference Measures for Exponential-Family Random Graph Models | ergm-references ergm.references ergmReference references-ergm references.ergm |
| Terms used in Exponential Family Random Graph Models | ergm-terms ergm.terms ergmTerm InitErgmTerm InitErgmWtTerm terms-ergm terms.ergm |
| Directed edgewise shared partners | desp-ergmTerm esp-ergmTerm InitErgmTerm.desp InitErgmTerm.esp |
| Exponentiate a network's statistic | Exp-ergmTerm InitErgmTerm.Exp InitWtErgmTerm.Exp |
| Filtering on arbitrary one-term model | F-ergmTerm InitErgmTerm.F |
| Faux desert High School as a network object | faux.desert.high |
| Faux dixon High School as a network object | faux.dixon.high |
| Goodreau's Faux Magnolia High School as a network object | faux.magnolia.high |
| Goodreau's Faux Mesa High School as a network object | faux.mesa.high fauxhigh |
| Convert a curved ERGM into a corresponding "fixed" ERGM. | fix.curved fix.curved.ergm fix.curved.formula |
| Preserve the dyad status in all but the given edges | fixallbut-ergmConstraint InitErgmConstraint.fixallbut |
| Fix specific dyads | fixedas-ergmConstraint InitErgmConstraint.fixedas |
| Florentine Family Marriage and Business Ties Data as a "network" object | flobusiness flomarriage florentine |
| A 'for' operator for terms | For-ergmTerm InitErgmTerm.For |
| Goodreau's four node network as a "network" object | g4 |
| Multivariate version of 'coda''s 'coda::geweke.diag()'. | geweke.diag.mv |
| Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model | gof gof.default gof.ergm gof.formula plot.gof print.gof |
| Number of dyads with values strictly greater than a threshold | greaterthan-ergmTerm InitWtErgmTerm.greaterthan |
| Geometrically weighted degree distribution for the first mode in a bipartite network | gwb1degree-ergmTerm InitErgmTerm.gwb1degree |
| Geometrically weighted dyadwise shared partner distribution for dyads in the first bipartition | gwb1dsp-ergmTerm InitErgmTerm.gwb1dsp |
| Geometrically weighted degree distribution for the second mode in a bipartite network | gwb2degree-ergmTerm InitErgmTerm.gwb2degree |
| Geometrically weighted dyadwise shared partner distribution for dyads in the second bipartition | gwb2dsp-ergmTerm InitErgmTerm.gwb2dsp |
| Geometrically weighted degree distribution | gwdegree-ergmTerm InitErgmTerm.gwdegree |
| Geometrically weighted dyadwise shared partner distribution | dgwdsp-ergmTerm gwdsp-ergmTerm InitErgmTerm.dgwdsp InitErgmTerm.gwdsp |
| Geometrically weighted edgewise shared partner distribution | dgwesp-ergmTerm gwesp-ergmTerm InitErgmTerm.dgwesp InitErgmTerm.gwesp |
| Geometrically weighted in-degree distribution | gwidegree-ergmTerm InitErgmTerm.gwidegree |
| Geometrically weighted non-edgewise shared partner distribution | dgwnsp-ergmTerm gwnsp-ergmTerm InitErgmTerm.dgwnsp InitErgmTerm.gwnsp |
| Geometrically weighted out-degree distribution | gwodegree-ergmTerm InitErgmTerm.gwodegree |
| Preserve the hamming distance to the given network (BROKEN: Do NOT Use) | hamming-ergmConstraint InitErgmConstraint.hamming |
| Hamming distance | hamming-ergmTerm InitErgmTerm.hamming |
| In-degree range | idegrange-ergmTerm InitErgmTerm.idegrange |
| In-degree | idegree-ergmTerm InitErgmTerm.idegree |
| In-degree to the 3/2 power | idegree1.5-ergmTerm InitErgmTerm.idegree1.5 |
| Preserve the indegree distribution | idegreedist-ergmConstraint InitErgmConstraint.idegreedist |
| Preserve indegree for directed networks | idegrees-ergmConstraint InitErgmConstraint.idegrees |
| Number of dyads whose values are in an interval | ininterval-ergmTerm InitWtErgmTerm.ininterval |
| Intransitive triads | InitErgmTerm.intransitive intransitive-ergmTerm |
| Testing for curved exponential family | is.curved is.curved.ergm is.curved.formula is.curved.NULL |
| Testing for dyad-independence | is.dyad.independent is.dyad.independent.ergm is.dyad.independent.ergm_conlist is.dyad.independent.formula is.dyad.independent.NULL |
| Function to check whether an ERGM fit or some aspect of it is valued | is.valued is.valued.edgelist is.valued.ergm is.valued.ergm_state is.valued.network |
| Isolated edges | InitErgmTerm.isolatededges isolatededges-ergmTerm |
| Isolates | InitErgmTerm.isolates isolates-ergmTerm |
| In-stars | InitErgmTerm.istar istar-ergmTerm |
| Kapferer's tailor shop data | kapferer kapferer2 tailor |
| k-stars | InitErgmTerm.kstar kstar-ergmTerm |
| Modify terms' coefficient names | InitErgmTerm.Label InitWtErgmTerm.Label Label-ergmTerm |
| Triangles within neighborhoods | InitErgmTerm.localtriangle localtriangle-ergmTerm |
| Take a natural logarithm of a network's statistic | InitErgmTerm.Log InitWtErgmTerm.Log Log-ergmTerm |
| A 'logLik()' method for 'ergm' fits. | AIC.ergm BIC.ergm deviance.ergm logLik.ergm |
| Calculate the null model likelihood | logLikNull logLikNull.ergm |
| Mixed 2-stars, a.k.a 2-paths | InitErgmTerm.m2star m2star-ergmTerm |
| Conduct MCMC diagnostics on a model fit | mcmc.diagnostics mcmc.diagnostics.default mcmc.diagnostics.ergm |
| Mean vertex degree | InitErgmTerm.meandeg meandeg-ergmTerm |
| Mixing matrix cells and margins | InitErgmTerm.mm InitWtErgmTerm.mm mm-ergmTerm |
| Synthetic network with 20 nodes and 28 edges | molecule |
| Mutuality | InitErgmTerm.mutual InitWtErgmTerm.mutual mutual-ergmTerm |
| Near simmelian triads | InitErgmTerm.nearsimmelian nearsimmelian-ergmTerm |
| A convenience container for a list of 'network' objects, output by 'simulate.ergm()' among others. | network.list print.network.list summary.network.list |
| Specifying nodal attributes and their levels | attr attrname attrs by COLLAPSE_SMALLEST LARGEST nodal.attr nodal.attribute nodal_attributes node.attr node.attribute on SMALLEST vertex.attr vertex.attribute |
| Main effect of a covariate | InitErgmTerm.nodecov InitErgmTerm.nodemain InitWtErgmTerm.nodecov InitWtErgmTerm.nodemain nodecov-ergmTerm nodemain-ergmTerm |
| Covariance of undirected dyad values incident on each actor | InitWtErgmTerm.nodecovar nodecovar-ergmTerm nodesqrtcovar-ergmTerm |
| Factor attribute effect | InitErgmTerm.nodefactor InitWtErgmTerm.nodefactor nodefactor-ergmTerm |
| Main effect of a covariate for in-edges | InitErgmTerm.nodeicov InitWtErgmTerm.nodeicov nodeicov-ergmTerm |
| Covariance of in-dyad values incident on each actor | InitWtErgmTerm.nodeicovar nodeicovar-ergmTerm nodeisqrtcovar-ergmTerm |
| Factor attribute effect for in-edges | InitErgmTerm.nodeifactor InitWtErgmTerm.nodeifactor nodeifactor-ergmTerm |
| Uniform homophily and differential homophily | InitErgmTerm.nodematch InitWtErgmTerm.match InitWtErgmTerm.nodematch match-ergmTerm nodematch-ergmTerm |
| Filtering on nodematch | InitErgmTerm.NodematchFilter NodematchFilter-ergmTerm |
| Nodal attribute mixing | InitErgmTerm.nodemix InitWtErgmTerm.nodemix nodemix-ergmTerm |
| Main effect of a covariate for out-edges | InitErgmTerm.nodeocov InitWtErgmTerm.nodeocov nodeocov-ergmTerm |
| Covariance of out-dyad values incident on each actor | InitWtErgmTerm.nodeocovar nodeocovar-ergmTerm |
| Factor attribute effect for out-edges | InitErgmTerm.nodeofactor InitWtErgmTerm.nodeofactor nodeofactor-ergmTerm |
| Length of the parameter vector associated with an object or with its terms. | nparam nparam.default nparam.ergm |
| Directed non-edgewise shared partners | dnsp-ergmTerm InitErgmTerm.dnsp InitErgmTerm.nsp nsp-ergmTerm |
| Preserve the observed dyads of the given network | InitErgmConstraint.observed observed-ergmConstraint |
| Out-degree range | InitErgmTerm.odegrange odegrange-ergmTerm |
| Out-degree | InitErgmTerm.odegree odegree-ergmTerm |
| Out-degree to the 3/2 power | InitErgmTerm.odegree1.5 odegree1.5-ergmTerm |
| Preserve the outdegree distribution | InitErgmConstraint.odegreedist odegreedist-ergmConstraint |
| Preserve outdegree for directed networks | InitErgmConstraint.odegrees odegrees-ergmConstraint |
| Terms with fixed coefficients | InitErgmTerm.Offset Offset-ergmTerm |
| Open triads | InitErgmTerm.opentriad opentriad-ergmTerm |
| k-Outstars | InitErgmTerm.ostar ostar-ergmTerm |
| Names of the parameters associated with an object. | param_names param_names.default param_names<- |
| ERGM-based tie probabilities | predict.ergm predict.formula |
| A product (or an arbitrary power combination) of one or more formulas | InitErgmTerm.Prod InitWtErgmTerm.Prod Prod-ergmTerm |
| A lack-of-fit test for ERGMs | rank_test.ergm |
| Receiver effect | InitErgmTerm.receiver InitWtErgmTerm.receiver receiver-ergmTerm |
| Evaluation on an induced subgraph | InitErgmTerm.S S-ergmTerm |
| Longitudinal networks of positive affection within a monastery as a "network" object | samplk samplk1 samplk2 samplk3 |
| Cumulative network of positive affection within a monastery as a "network" object | samplike sampson |
| Generate networks with a given set of network statistics | san san.default san.ergm_model san.formula |
| Search ERGM terms, constraints, references, hints, and proposals | search.ergmConstraints search.ergmHints search.ergmProposals search.ergmReferences search.ergmTerms |
| Sender effect | InitErgmTerm.sender InitWtErgmTerm.sender sender-ergmTerm |
| Simmelian triads | InitErgmTerm.simmelian simmelian-ergmTerm |
| Ties in simmelian triads | InitErgmTerm.simmelianties simmelianties-ergmTerm |
| Draw from the distribution of an Exponential Family Random Graph Model | .simulate_formula.network simulate.ergm simulate.ergm_model simulate.ergm_state simulate.ergm_state_full simulate.formula.ergm simulate.formula_lhs_network simulate_formula simulate_formula.ergm_state simulate_formula.network |
| A 'simulate' Method for 'formula' objects that dispatches based on the Left-Hand Side | simulate.formula simulate.formula_lhs |
| Number of ties between actors with similar attribute values | InitErgmTerm.smalldiff smalldiff-ergmTerm |
| Number of dyads with values strictly smaller than a threshold | InitWtErgmTerm.smallerthan smallerthan-ergmTerm |
| Statnet Control | snctrl |
| Undirected degree | InitErgmTerm.sociality InitWtErgmTerm.sociality sociality-ergmTerm |
| Sparse network | InitErgmConstraint.sparse sparse-ergmConstraint sparse-ergmHint |
| Multivariate version of 'coda''s 'spectrum0.ar()'. | spectrum0.mvar |
| Standard Normal reference | InitErgmReference.StdNormal StdNormal-ergmReference |
| Stratify Proposed Toggles by Mixing Type on a Vertex Attribute | InitErgmConstraint.strat strat-ergmConstraint strat-ergmHint |
| Sum of dyad values (optionally taken to a power) | InitWtErgmTerm.sum sum-ergmTerm |
| A sum (or an arbitrary linear combination) of one or more formulas | InitErgmTerm.Sum InitWtErgmTerm.Sum Sum-ergmTerm |
| Summarizing ERGM Model Fits | print.summary.ergm summary.ergm |
| Calculation of network or graph statistics or other attributes specified on a formula | summary summary.formula |
| Evaluation on symmetrized (undirected) network | InitErgmTerm.Symmetrize Symmetrize-ergmTerm |
| Three-trails | InitErgmTerm.threepath InitErgmTerm.threetrail threepath-ergmTerm threetrail-ergmTerm |
| Transitive triads | InitErgmTerm.transitive transitive-ergmTerm |
| Transitive ties | InitErgmTerm.transitiveties transitiveties-ergmTerm |
| Transitive weights | InitWtErgmTerm.transitiveweights transitiveweights-ergmTerm |
| Triad census | InitErgmTerm.triadcensus triadcensus-ergmTerm |
| Network with strong clustering (triad-closure) effects | .triadic-ergmHint InitErgmConstraint..triadic InitErgmConstraint.triadic triadic-ergmConstraint triadic-ergmHint |
| Triangles | InitErgmTerm.triangle triangle-ergmTerm triangles-ergmTerm |
| Triangle percentage | InitErgmTerm.tripercent tripercent-ergmTerm |
| Transitive triples | InitErgmTerm.ttriad InitErgmTerm.ttriple ttriad-ergmTerm ttriple-ergmTerm |
| 2-Paths | InitErgmTerm.twopath twopath-ergmTerm |
| Continuous Uniform reference | InitErgmReference.Unif Unif-ergmReference |
| Update the edges in a network based on a matrix | update.network update_network update_network.data.frame update_network.ergm_state update_network.matrix update_network.matrix_edgelist |
| Weighted Median | wtd.median |
