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

On CRAN:

36 exports 5 stars 1.41 score 40 dependencies 72 scripts 1.3k downloads

Last updated 9 months agofrom:202b0aa953. Checks:OK: 1 WARNING: 8. Indexed: yes.

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