Package: networkscaleup 0.1-2
networkscaleup: Network Scale-Up Models for Aggregated Relational Data
Provides a variety of Network Scale-up Models for researchers to analyze Aggregated Relational Data, mostly through the use of Stan. In this version, the package implements models from Laga, I., Bao, L., and Niu, X (2021) <arxiv:2109.10204>, 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:
networkscaleup_0.1-2.tar.gz
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networkscaleup.pdf |networkscaleup.html✨
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
- example_data - Simulated ARD data set with z and x.
Last updated 9 months agofrom:b3ca2abda0. Checks:ERROR: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Oct 26 2024 |
R-4.5-win-x86_64 | NOTE | Oct 26 2024 |
R-4.5-linux-x86_64 | NOTE | Oct 26 2024 |
R-4.4-win-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-aarch64 | NOTE | Oct 26 2024 |
R-4.3-win-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-aarch64 | NOTE | Oct 26 2024 |
Exports:correlatedStankillworthoverdispersedoverdispersedStanscaling
Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelingLaplacesDemonlatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr
Fitting Network Scale-up Models
Rendered fromFittingNetworkScaleup.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2022-10-10
Started: 2022-10-10