networktree: Recursive Partitioning of Network Models (original) (raw)
Network trees recursively partition the data with respect to covariates. Two network tree algorithms are available: model-based trees based on a multivariate normal model and nonparametric trees based on covariance structures. After partitioning, correlation-based networks (psychometric networks) can be fit on the partitioned data. For details see Jones, Mair, Simon, & Zeileis (2020) <doi:10.1007/s11336-020-09731-4>.
| Version: | 1.0.1 |
|---|---|
| Depends: | R (≥ 3.5.0) |
| Imports: | partykit, qgraph, stats, utils, Matrix, mvtnorm, Formula, grid, graphics, gridBase, reshape2 |
| Suggests: | R.rsp, knitr, rmarkdown, fxregime, zoo |
| Published: | 2021-02-04 |
| DOI: | 10.32614/CRAN.package.networktree |
| Author: | Payton Jones  [aut, cre], Thorsten Simon [aut], Achim Zeileis [aut] |
| Maintainer: | Payton Jones |
| BugReports: | https://github.com/paytonjjones/networktree/issues |
| License: | GPL-2 | GPL-3 |
| URL: | https://paytonjjones.github.io/networktree/ |
| NeedsCompilation: | no |
| Citation: | networktree citation info |
| Materials: | NEWS |
| In views: | Psychometrics |
| CRAN checks: | networktree results |
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