Package: netcom 2.1.6

netcom: NETwork COMparison Inference

Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <arxiv:1912.12551>.

Authors:Ryan Langendorf [aut, cre], Debra Goldberg [ctb], Matthew Burgess [ctb]

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Peer review:

Bug tracker:https://github.com/langendorfr/netcom/issues

On CRAN:

34 exports 5 stars 1.23 score 71 dependencies 71 scripts 791 downloads

Last updated 2 months agofrom:bc0b912255. Checks:ERROR: 7. Indexed: yes.

Exports:%>%alignbest_fit_optimclassifyclassify_Systematiccomparecompare_Targetginigrow_DDgrow_DMgrow_ERgrow_NMgrow_PAgrow_SWicsmake_DDmake_DMmake_Mixturemake_NMmake_Nullmake_Null_canonicalmake_Null_mixturemake_SWmake_Systematicmake_Systematic_canonicalmake_Systematic_directedCanonicalLikemake_Systematic_mixturenull_fit_optimstir_DDstir_DMstir_ERstir_NMstir_PAstir_SW

Dependencies:cachemcliclueclustercodetoolscolorspacecpp11doParalleldplyrexpmfansifarverfastmapforeachgenericsGenSAggforceggfortifyggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmunsellnlmenloptrnumDerivoptimxpdistpermutepillarpkgconfigplyrpolyclippracmapurrrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangscalesstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsveganviridisviridisLitewithr