Package: VBLPCM 2.4.9

Michael Salter-Townshend

VBLPCM: Variational Bayes Latent Position Cluster Model for Networks

Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation developed in Salter-Townshend and Murphy (2013) <doi:10.1016/j.csda.2012.08.004>.

Authors:Michael Salter-Townshend

VBLPCM_2.4.9.tar.gz
VBLPCM_2.4.9.tar.gz(r-4.5-noble)VBLPCM_2.4.9.tar.gz(r-4.4-noble)
VBLPCM_2.4.9.tgz(r-4.4-emscripten)VBLPCM_2.4.9.tgz(r-4.3-emscripten)
VBLPCM.pdf |VBLPCM.html✨
VBLPCM/json (API)
NEWS

# Install 'VBLPCM' in R:
install.packages('VBLPCM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • gsl– GNU Scientific Library (GSL)
Datasets:
  • Y - Simulated.network
  • aids.net - Aids blogs data as a "network" object
  • samplike - Cumulative network of positive affection within a monastery as a "network" object

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.66 score 2 stars 23 scripts 292 downloads 20 exports 37 dependencies

Last updated 2 years agofrom:a6dcea1354. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64OKNov 20 2024

Exports:E_to_Yfruchterman_reingoldgof.vblpcmhops_to_hopslistlog_like_forcesplot.vblpcmpredict.vblpcmprint.vblpcmsummary.vblpcmvblpcmbicvblpcmcovsvblpcmdrawpievblpcmfitvblpcmgroupsvblpcmKLvblpcmrocvblpcmstartY_to_EY_to_MY_to_nonE

Dependencies:cachemclicodaDEoptimRergmevaluatefansifastmapgluehighrknitrlatticelifecyclelpSolveAPImagrittrMatrixmclustmemoisenetworkpillarpkgconfigpurrrrbibutilsRdpackrlangrlerobustbasesnastatnet.commonstringistringrtibbletrustutf8vctrsxfunyaml

Readme and manuals

Help Manual

Help pageTopics
VBLPCM: Variational Bayes for the Latent Position Cluster Model for networksVBLPCM-package VBLPCM
aids blogs data as a ``network" objectaids aids.net
create an adjacency matrix from an edgelist.E_to_Y
Perform Fruchterman-Reingold layout of a network in 2 or more dimensions.fruchterman_reingold
Goodness of fit based on simulations from the fitted object.gof.vblpcm
create a handy matrix of vectors to store the hopslisthops_to_hopslist
create an initial configuration for the latent positions.log_like_forces
plot the posterior latent positions and groupings and networkplot.vblpcm
Find all link probabilitiespredict.vblpcm
print the fitted vblpcm objectprint.vblpcm
Cumulative network of positive affection within a monastery as a ``network'' objectsamplike sampson
simulated.networkY
summary of a fitted vblpcm object.summary.vblpcm
calculate the BIC for the fitted VBLPCM objectvblpcmbic
create the design matrix for the network analysisvblpcmcovs
add a piechart of group memberships of a node to a network plot; taken mainly from latentnet equivalentvblpcmdrawpie
fit the variational model through EM type iterationsvblpcmfit
list the maximum VB a-posteriori group memberships.vblpcmgroups
print and returns the Kullback-Leibler divergence from the fitted vblpcm object to the true LPCM posteriorvblpcmKL
ROC curve plot for vblpcmfitvblpcmroc
Generate sensible starting configuration for the variational parameter set.vblpcmstart
calculate the edgelist for a given adjacency matrixY_to_E
calculate the missing edges as an edgelist from an adjacency matrix with NaNs indicating missing linksY_to_M
calculate a non-edge list from an adjacency matrixY_to_nonE