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) .


News

networktree 0.2.1

  • bug fix for plots, fill lower triangular of matrix first
  • dots of plot method now parsed to terminal layout
  • fixed a bug when using different data types in nodevars & splitvars
  • added 'getnetwork' function to easily extract networks

Reference manual

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install.packages("networktree")

1.0.1 by Payton Jones, 8 months ago


https://paytonjjones.github.io/networktree/


Report a bug at https://github.com/paytonjjones/networktree/issues


Browse source code at https://github.com/cran/networktree


Authors: Payton Jones [aut, cre] , Thorsten Simon [aut] , Achim Zeileis [aut]


Documentation:   PDF Manual  


Task views: Psychometric Models and Methods


GPL-2 | GPL-3 license


Imports partykit, qgraph, stats, utils, Matrix, mvtnorm, Formula, grid, graphics, gridBase, reshape2

Suggests R.rsp, knitr, rmarkdown, fxregime, zoo


See at CRAN