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>
License: GPL-3
NeedsCompilation: no
Citation: tnet citation info
Materials: ChangeLog
In views: CausalInference
CRAN checks: tnet results


Reference manual: tnet.pdf


Package source: tnet_3.0.16.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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