Package: nett 1.0.0

nett: Network Analysis and Community Detection

Features tools for the network data analysis and community detection. Provides multiple methods for fitting, model selection and goodness-of-fit testing in degree-corrected stochastic blocks models. Most of the computations are fast and scalable for sparse networks, esp. for Poisson versions of the models. Implements the following: Amini, Chen, Bickel and Levina (2013) <doi:10.1214/13-AOS1138> Bickel and Sarkar (2015) <doi:10.1111/rssb.12117> Lei (2016) <doi:10.1214/15-AOS1370> Wang and Bickel (2017) <doi:10.1214/16-AOS1457> Zhang and Amini (2020) <arxiv:2012.15047> Le and Levina (2022) <doi:10.1214/21-EJS1971>.

Authors:Arash A. Amini [aut, cre], Linfan Zhang [aut]

nett_1.0.0.tar.gz
nett_1.0.0.zip(r-4.7-x86_64)nett_1.0.0.zip(r-4.7-arm64)nett_1.0.0.zip(r-4.6-x86_64)nett_1.0.0.zip(r-4.6-arm64)nett_1.0.0.zip(r-4.5-x86_64)
nett_1.0.0.tgz(r-4.6-x86_64)nett_1.0.0.tgz(r-4.6-arm64)nett_1.0.0.tgz(r-4.5-x86_64)nett_1.0.0.tgz(r-4.5-arm64)
nett_1.0.0.tar.gz(r-4.7-arm64)nett_1.0.0.tar.gz(r-4.7-x86_64)nett_1.0.0.tar.gz(r-4.6-arm64)nett_1.0.0.tar.gz(r-4.6-x86_64)
nett_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
nett/json (API)

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

Bug tracker:https://github.com/aaamini/nett/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

5.64 score 8 stars 27 scripts 352 downloads 38 exports 8 dependencies

Last updated from:35b0441c8c. Checks:13 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE131
linux-devel-x86_64NOTE163
source / vignettesOK341
linux-release-arm64NOTE182
linux-release-x86_64NOTE166
macos-release-arm64NOTE156
macos-release-x86_64NOTE277
macos-oldrel-arm64NOTE129
macos-oldrel-x86_64NOTE248
windows-devel-arm64NOTE253
windows-devel-x86_64NOTE207
windows-release-arm64NOTE220
windows-release-x86_64NOTE141
windows-oldrel-x86_64NOTE151
wasm-releaseOK109

Exports:%>%adj_spec_testbethe_hessian_selectcompute_block_sumscompute_confusion_matrixcompute_mutual_infoestim_dcsbmeval_dcsbm_biceval_dcsbm_likeeval_dcsbm_loglrextract_largest_ccextract_low_deg_compfast_cplfast_sbmgen_rand_connget_dcsbm_exav_deglabel_mat2veclabel_vec2matnac_testplot_deg_distplot_netplot_rocplot_smooth_profilepp_connprintfrsympermsample_dcersample_dclvmsample_dcppsample_dcsbmsample_tdcsbmsimulate_rocsinkhorn_knoppsnac_resamplesnac_selectsnac_testspec_clustspec_repr

Dependencies:codetoolsforeachiteratorslatticemagrittrMatrixRcppRcppArmadillo

Visualization
Visualizing a DCSBM | A latent variable model | Visualizing Political Blogs network
Rendered fromVisualization.Rmdusingknitr::rmarkdown

Last update: 2022-10-22
Started: 2020-12-17

Exploring Community Structure
Rendered fromexplore-comm.Rmdusingknitr::rmarkdown

Last update: 2022-10-01
Started: 2021-01-01

A hard DCSBM testing problem
Setup and models | Sinkhorn construction | Generating from the models | Verifying equality of expected degrees | Performance of NAC tests | Results | Comments | References
Rendered fromhard_dcsbm_testing.Rmdusingknitr::rmarkdown

Last update: 2022-09-30
Started: 2021-01-21

Community detection
Spectral clustering | Performance as a function of the expected degree | Simple planted partition model | Randomly permuted connectivity matrix
Rendered fromCommunity_Detection.Rmdusingknitr::rmarkdown

Last update: 2022-09-24
Started: 2020-12-29

Readme and manuals

Help Manual

Help pageTopics
Adjusted spectral testadj_spec_test
Beth-Hessian model selectionbethe_hessian_select
Block sum of an adjacency matrixcompute_block_sums
Compute confusion matrixcompute_confusion_matrix
Compute normalized mutual information (NMI)compute_mutual_info
Estimate model parameters of a DCSBMestim_dcsbm
Compute BIC scoreeval_dcsbm_bic
Log likelihood of a DCSBM (fast with poi = TRUE)eval_dcsbm_like
Log-likelihood ratio of two DCSBMs (fast with poi = TRUE)eval_dcsbm_loglr
Extract largest componentextract_largest_cc
Extract low-degree componentextract_low_deg_comp
CPL algorithm for community detection (fast)fast_cpl
Sample from a SBM (fast)fast_sbm
Generate randomly permuted connectivity matrixgen_rand_conn
Calculate the expected average degree of a DCSBMget_dcsbm_exav_deg
Convert label matrix to vectorlabel_mat2vec
Convert label vector to matrixlabel_vec2mat
NAC testnac_test
Plot degree distributionplot_deg_dist
Plot a networkplot_net
Plot ROC curvesplot_roc
Plot community profilesplot_smooth_profile
Political blogs networkpolblogs
Generate planted partition (PP) connectivity matrixpp_conn
The usual "printf" functionprintf
Generate random symmetric permutation matrixrsymperm
Sample from a DCERsample_dcer
Sample from a DCLVMsample_dclvm
Sample from a DCPPsample_dcpp
Sample from a DCSBMsample_dcsbm
Sample truncated DCSBM (fast)sample_tdcsbm
Simulate data to estimate ROC curvessimulate_roc
Sinkhorn-Knopp matrix scalingsinkhorn_knopp
Resampled SNAC+snac_resample
Estimate community number with SNAC+snac_select
SNAC testsnac_test
Spectral clustering (fast)spec_clust
Spectral Representationspec_repr