Package: latentnet 2.11.0-1649
Pavel N. Krivitsky
latentnet: Latent Position and Cluster Models for Statistical Networks
Fit and simulate latent position and cluster models for statistical networks. See Krivitsky and Handcock (2008) <doi:10.18637/jss.v024.i05> and Krivitsky, Handcock, Raftery, and Hoff (2009) <doi:10.1016/j.socnet.2009.04.001>.
Authors:
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latentnet.pdf |latentnet.html✨
latentnet/json (API)
NEWS
| # Install 'latentnet' in R: |
| install.packages('latentnet', repos = c('https://statnet.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/statnet/latentnet/issues
Last updated 13 days agofrom:e6b5922503. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 05 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 05 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 05 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 05 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 05 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 05 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 05 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 05 2024 |
Exports:as.ergmm.par.listbic.ergmmcontrol.ergmmergmmergmm.controlergmm.drawpieergmm.priorshow.ergmm
Dependencies:abindcachemclicodaDEoptimRergmevaluatefansifastmapgluehighrknitrlatticelifecyclelpSolveAPImagrittrMASSMatrixmemoisemvtnormnetworkpillarpkgconfigpurrrrbibutilsRdpackrlangrlerobustbasesnastatnet.commonstringistringrtibbletrustutf8vctrsxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| latentnet: Latent Position and Cluster Models for Statistical Networks | latentnet-package latentnet |
| Convert an ERGMM Object to an MCMC list object for Diagnostics. | as.mcmc.ergmm as.mcmc.list.ergmm |
| Bilinear (inner-product) latent space, with optional clustering | bilinear-ergmTerm InitErgmTerm.bilinear |
| Auxiliary for Controlling ERGMM Fitting | control.ergmm ergmm.control |
| Southern Women Data Set (Davis) as a bipartite ``network'' object | davis |
| Fit a Latent Space Random Graph Model | ergmm latent latentcluster |
| Class of Fitted Exponential Random Graph Mixed Models | ergmm-class ergmm.object print.ergmm show.ergmm |
| Edge Weight Distribution Families | dlpY.ddispersion.fs dlpY.ddispersion.normal.identity dlpY.deta.Bernoulli.logit dlpY.deta.binomial.logit dlpY.deta.fs dlpY.deta.normal.identity dlpY.deta.Poisson.log ergmm-families ergmm.families EY.Bernoulli.logit EY.binomial.logit EY.fs EY.normal.identity EY.Poisson.log fam.par.check families.ergmm family family.IDs family.names lpY.Bernoulli.logit lpY.binomial.logit lpY.fs lpY.normal.identity lpY.Poisson.log lpYc.Bernoulli.logit lpYc.binomial.logit lpYc.fs lpYc.normal.identity lpYc.Poisson.log pY.Bernoulli.logit pY.binomial.logit pY.fs pY.normal.identity pY.Poisson.log rsm.Bernoulli.logit rsm.binomial.logit rsm.fs rsm.normal.identity rsm.Poisson.log |
| Draw a pie chart at a specified location. | ergmm.drawpie |
| A List of ERGMM Parameter Configuration | $.ergmm.par.list as.ergmm.par.list as.mcmc.list.ergmm.par.list del.iteration ergmm.par.list ergmm.par.list.object length.ergmm.par.list unstack.ergmm.par.list [.ergmm.par.list [[.ergmm.par.list |
| Auxiliary for Setting the ERGMM Prior | ergmm.prior |
| Euclidean distance latent space, with optional clustering | euclidean-ergmTerm InitErgmTerm.euclidean |
| Squared euclidean distance latent space, with optional clustering | euclidean2-ergmTerm InitErgmTerm.euclidean2 |
| Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Mixed Model Fit | gof gof.ergmm |
| Intercept | 1-ergmTerm InitErgmTerm.Intercept Intercept-ergmTerm intercept-ergmTerm |
| Edge covariates for the latent model | InitErgmTerm.latentcov latentcov-ergmTerm |
| Covariate effect on self-loops | InitErgmTerm.loopcov loopcov-ergmTerm |
| Factor attribute effect on self-loops | InitErgmTerm.loopfactor loopfactor-ergmTerm |
| Self-loops | InitErgmTerm.loops loops-ergmTerm |
| Conduct MCMC diagnostics on an ERGMM fit | mcmc.diagnostics mcmc.diagnostics.ergmm |
| Merge two or more replications of ERGMM fits | merge.ergmm |
| Plotting Method for class ERGMM | plot.ergmm plot3d.ergmm |
| Predicted Dyad Values for an ERGMM. | predict.ergmm |
| Receiver covariate effect | InitErgmTerm.receivercov receivercov-ergmTerm |
| Random receiver effect | InitErgmTerm.rreceiver rreceiver-ergmTerm |
| Random sender effect | InitErgmTerm.rsender rsender-ergmTerm |
| Random sociality effect | InitErgmTerm.rsociality rsociality-ergmTerm |
| Sender covariate effect | InitErgmTerm.sendercov sendercov-ergmTerm |
| Draw from the distribution of an Exponential Random Graph Mixed Model | simulate simulate.ergmm simulate.ergmm.model |
| Sociality covariate effect | InitErgmTerm.socialitycov socialitycov-ergmTerm |
| ERGMM Fit Summaries | bic.ergmm print.summary.ergmm summary.ergmm summary.ergmm.object |
| Read Highland Tribes | tribes |
