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tnet: Weighted, Two-Mode, and Longitudinal Networks Analysis

Binary ties limit the richness of network analyses as relations are unique. The two-mode structure contains a number of features lost when projection it to a one-mode network. Longitudinal datasets allow for an understanding of the causal relationship among ties, which is not the case in cross-sectional datasets as ties are dependent upon each other.

Version: 3.0.16
Depends: R (≥ 2.13.0), igraph, survival
Published: 2020-02-24
DOI: 10.32614/CRAN.package.tnet
Author: Tore Opsahl
Maintainer: Tore Opsahl <tore at opsahl.co.uk>
License: GPL-3
URL: http://toreopsahl.com/tnet/
NeedsCompilation: no
Citation: tnet citation info
Materials: ChangeLog
In views: CausalInference
CRAN checks: tnet results

Documentation:

Reference manual: tnet.pdf

Downloads:

Package source: tnet_3.0.16.tar.gz
Windows binaries: r-devel: tnet_3.0.16.zip, r-release: tnet_3.0.16.zip, r-oldrel: tnet_3.0.16.zip
macOS binaries: r-release (arm64): tnet_3.0.16.tgz, r-oldrel (arm64): tnet_3.0.16.tgz, r-release (x86_64): tnet_3.0.16.tgz, r-oldrel (x86_64): tnet_3.0.16.tgz
Old sources: tnet archive

Reverse dependencies:

Reverse imports: Cascade, ITNr, Patterns, SPONGE

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tnet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.