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networktree: Recursive Partitioning of Network Models
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 |
| Author: |
Payton Jones 
[aut, cre],
Thorsten Simon
[aut],
Achim Zeileis
[aut] |
| Maintainer: |
Payton Jones <paytonjjones at gmail.com> |
| 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 |
Documentation:
Downloads:
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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.
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