Package: lolog 1.3.2

Ian E. Fellows

lolog: Latent Order Logistic Graph Models

Estimation of Latent Order Logistic (LOLOG) Models for Networks. LOLOGs are a flexible and fully general class of statistical graph models. This package provides functions for performing MOM, GMM and variational inference. Visual diagnostics and goodness of fit metrics are provided. See Fellows (2018) <arxiv:1804.04583> for a detailed description of the methods.

Authors:Ian E. Fellows [aut, cre], Mark S. Handcock [ctb]

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lolog.pdf |lolog.html
lolog/json (API)

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

Peer review:

Bug tracker:https://github.com/statnet/lolog/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • lazega - Collaboration Relationships Among Partners at a New England Law Firm
  • ukFaculty - Friendship network of a UK university faculty

On CRAN:

5.86 score 5 stars 72 scripts 691 downloads 36 exports 40 dependencies

Last updated 11 months agofrom:202b0aa953. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64WARNINGNov 06 2024
R-4.5-linux-x86_64WARNINGNov 06 2024
R-4.4-win-x86_64WARNINGNov 06 2024
R-4.4-mac-x86_64WARNINGNov 06 2024
R-4.4-mac-aarch64WARNINGNov 06 2024
R-4.3-win-x86_64WARNINGNov 06 2024
R-4.3-mac-x86_64WARNINGNov 06 2024
R-4.3-mac-aarch64WARNINGNov 06 2024

Exports:_lolog_initStats_rcpp_module_boot_lologas.BinaryNetas.BinaryNet.defaultas.networkas.network.Rcpp_DirectedNetas.network.Rcpp_UndirectedNetcalculateStatisticscoef.lologcreateCppModelcreateLatentOrderLikelihoodDirectedLatentOrderLikelihoodDirectedModelDirectedNetgofitgofit.lologinitLologStatisticsinlineLologPluginlologlologPackageSkeletonlologVariationalplot.gofitplot.lologGmmplot.Rcpp_DirectedNetplot.Rcpp_UndirectedNetprint.gofitprint.lologprint.lologVariationalFitregisterDirectedStatisticregisterUndirectedStatisticrunLologCppTestssimulate.lologsummary.lologUndirectedLatentOrderLikelihoodUndirectedModelUndirectedNet

Dependencies:BHclicodacolorspacecpp11fansifarverggplot2gluegtableigraphintergraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnetworknlmepillarpkgconfigplyrR6RColorBrewerRcppreshape2rlangscalesstatnet.commonstringistringrtibbleutf8vctrsviridisLitewithr

An Example Analysis Using LOLOG

Rendered fromlolog-ergm.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-01-03
Started: 2018-04-10

An Introduction to Latent Order Logistic (LOLOG) Network Models

Rendered fromlolog-introduction.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2020-12-16
Started: 2018-03-21

Readme and manuals

Help Manual

Help pageTopics
indexing[ [,Rcpp_DirectedNet,ANY,ANY,ANY-method [,Rcpp_DirectedNet-method [,Rcpp_UndirectedNet,ANY,ANY,ANY-method [,Rcpp_UndirectedNet-method [<- [<-,Rcpp_DirectedNet,ANY,ANY,ANY-method [<-,Rcpp_DirectedNet-method [<-,Rcpp_UndirectedNet,ANY,ANY,ANY-method [<-,Rcpp_UndirectedNet-method \S4method{[<-}{Rcpp_DirectedNet,ANY,ANY,ANY} \S4method{[<-}{Rcpp_UndirectedNet,ANY,ANY,ANY} \S4method{[}{Rcpp_DirectedNet,ANY,ANY,ANY} \S4method{[}{Rcpp_UndirectedNet,ANY,ANY,ANY}
Convert to either an UndirectedNet or DirectedNet objectas.BinaryNet
Convert to either an UndirectedNet or DirectedNet objectas.BinaryNet.default
Network conversionas.network
Convert a DirectedNet to a network objectas.network.Rcpp_DirectedNet
Convert a UndirectedNet to a network objectas.network.Rcpp_UndirectedNet
BinaryNetBinaryNet DirectedNet Rcpp_DirectedNet-class Rcpp_UndirectedNet-class UndirectedNet
Calculate network statistics from a formulacalculateStatistics
Internal Symbolscall-symbols initLologStatistics runLologCppTests _lolog_initStats _rcpp_module_boot_lolog
Extracts estimated model coefficients.coef.lolog
Creates a modelcreateCppModel
Creates a probability model for a latent ordered network modelcreateLatentOrderLikelihood
Conduct goodness of fit diagnosticsgofit
Goodness of Fit Diagnostics for a LOLOG fitgofit.lolog
An lolog plug-in for easy C++ prototyping and accessinlineLologPlugin
LatentOrderLikelihoodDirectedLatentOrderLikelihood LatentOrderLikelihood Rcpp_DirectedLatentOrderLikelihood-class Rcpp_UndirectedLatentOrderLikelihood-class UndirectedLatentOrderLikelihood
Collaboration Relationships Among Partners at a New England Law Firmlazega
Fits a LOLOG model via Monte Carlo Generalized Method of Momentslolog
LOLOG Model Termslolog-terms
ModelsDirectedModel LologModels Rcpp_DirectedModel-class Rcpp_UndirectedModel-class UndirectedModel
Create a skeleton for a package extending lologlologPackageSkeleton
Fits a latent ordered network model using Monte Carlo variational inferencelologVariational
Plots a gofit objectplot.gofit
Conduct Monte Carlo diagnostics on a lolog model fitplot.lologGmm
plot an DirectedNet objectplot.Rcpp_DirectedNet
Plot an UndirectedNet objectplot.Rcpp_UndirectedNet
prints a gofit objectprint.gofit
Print a `lolog` objectprint.lolog
Print of a lologVariationalFit objectprint.lologVariationalFit
Register StatisticsregisterDirectedOffset registerDirectedStatistic registerUndirectedOffset registerUndirectedStatistic
Generates BinaryNetworks from a fit lolog objectsimulate.lolog
Summary of a `lolog` objectsummary.lolog
Friendship network of a UK university facultyukFaculty