Package: networkscaleup 0.2-2

networkscaleup: Network Scale-Up Models for Aggregated Relational Data

Provides a variety of Network Scale-up Models for researchers to analyze Aggregated Relational Data, through the use of Stan and 'glmmTMB'. Also provides tools for model checking In this version, the package implements models from Laga, I., Bao, L., and Niu, X (2023) <doi:10.1080/01621459.2023.2165929>, Zheng, T., Salganik, M. J., and Gelman, A. (2006) <doi:10.1198/016214505000001168>, Killworth, P. D., Johnsen, E. C., McCarty, C., Shelley, G. A., and Bernard, H. R. (1998) <doi:10.1016/S0378-8733(96)00305-X>, and Killworth, P. D., McCarty, C., Bernard, H. R., Shelley, G. A., and Johnsen, E. C. (1998) <doi:10.1177/0193841X9802200205>.

Authors:Ian Laga [aut, cre], Owen G. Ward [aut], Anna L. Smith [aut], Benjamin Vogel [aut], Jieyun Wang [aut], Le Bao [aut], Xiaoyue Niu [aut]

networkscaleup_0.2-2.tar.gz
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networkscaleup_0.2-2.tgz(r-4.6-x86_64)networkscaleup_0.2-2.tgz(r-4.6-arm64)networkscaleup_0.2-2.tgz(r-4.5-x86_64)networkscaleup_0.2-2.tgz(r-4.5-arm64)
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manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
networkscaleup/json (API)

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

Bug tracker:https://github.com/ilaga/networkscaleup/issues

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

On CRAN:

Conda:

cpp

4.81 score 4 stars 16 scripts 337 downloads 17 exports 106 dependencies

Last updated from:f24808647e. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK1166
linux-devel-x86_64OK1167
source / vignettesOK1556
linux-release-arm64OK1122
linux-release-x86_64OK1312
macos-release-arm64OK778
macos-release-x86_64OK2187
macos-oldrel-arm64OK811
macos-oldrel-x86_64OK1462
windows-develOK1748
windows-releaseOK1742
windows-oldrelOK1736
wasm-releaseFAIL210

Exports:construct_pearsonconstruct_rqrcorrelatedStancov_plotsdispersion_metricfit_mleget_surrogatehang_rootogram_ardkillworthmake_ardoverdispersedoverdispersedStanplot_fittedresidual_correlationresidual_heatmapscalingtw_group_corr_test

Dependencies:abindarrayhelpersbackportsBHbinombitbit64bootbroomcallrcheckmateclicliprcodacolorspacecowplotcpp11crayonDerivdescdistributionaldoBydplyrfarverforecastfracdiffgenericsggdistggplot2glmmTMBgluegridExtragtablegtoolshmsinlineisobandlabelingLaplacesDemonlatticelifecyclelme4lmtestloomagrittrMASSMatrixmatrixStatsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivotelpbkrtestpillarpkgbuildpkgconfigposteriorprettyunitsprocessxprogresspspurrrquadprogQuickJSRR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreadrreformulasrlangRMTstatrstanrstantoolsS7sandwichscalesStanHeadersstringistringrsvUnittensorAtibbletidybayestidyrtidyselecttimeDateTMBtrialrtzdburcautf8vctrsviridisLitevroomwithrzoo

Diagnostic tools for ARD Models
Simulating Data | Hanging Rootograms | Testing for Covariates

Last update: 2026-06-24
Started: 2026-06-24

Fitting Network Scale-up Models
Overview | Instructions | PIMLE | MLE | Bayesian Models | Overdispersed Model | Correlated Models

Last update: 2026-06-24
Started: 2022-10-10

Readme and manuals

Help Manual

Help pageTopics
Compute Pearson Residuals for ARD matrix and fitted modelconstruct_pearson
Compute Randomized Quantile Residuals for ARD Modelsconstruct_rqr
Fit ARD using the uncorrelated or correlated model in Stan This function fits the ARD using either the uncorrelated or correlated model in Laga et al. (2021) in Stan. The population size estimates and degrees are scaled using a post-hoc procedure.correlatedStan
Covariance plotscov_plots
Dispersion Metric for Fitted ARD Modeldispersion_metric
Simulated ARD data set with z and x.example_data
Fit basic Poisson and Negative Binomial models using glmmTMBfit_mle
Compute Surrogate Residuals for ARD Modelsget_surrogate
Hanging Rootogram for Fitted ARD Modelhang_rootogram_ard
Fit Killworth models to ARD. This function estimates the degrees and population sizes using the plug-in MLE and MLE estimator.killworth
log computed uniform quantilelog_mix_uniform
Generate simulated ARDmake_ard
Construct tibble from ARD matrixmake_ard_tidy
The 'networkscaleup' package.networkscaleup-package networkscaleup
Fit Overdispersed model to ARD (Gibbs-Metropolis)overdispersed
Fit ARD using the Overdispersed model in StanoverdispersedStan
Plot residuals against fitted valuesplot_fitted
Construction Residual (row/column) correlation matrixresidual_correlation
Construct heatmap of residualsresidual_heatmap
compute numerically stable negative binomial rqrrqr_nbinom_logs
compute numerically stable Poisson rqrrqr_pois_logs
Scale raw log degree and log prevalence estimatesscaling
Tracy-Widom test for residual group correlationtw_group_corr_test