The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data
Open accessAbstract
We present the R package mgm for the estimation of k-order mixed graphical models (MGMs) and mixed vector autoregressive (mVAR) models in high-dimensional data. These are a useful extensions of graphical models for only one variable type, since data sets consisting of mixed types of variables (continuous, count, categorical) are ubiquitous. In addition, we allow to relax the stationarity assumption of both models by introducing time-varying versions of MGMs and mVAR models based on a kernel weighting approach. Time-varying models offer a rich description of temporally evolving systems and allow to identify external influences on the model structure such as the impact of interventions. We provide the background of all implemented methods and provide fully reproducible examples that illustrate how to use the package.
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Cites
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Borsboom, D. (2017) · World Psychiatry · doi:10.1002/wps.20375 · Cited by 3,482
A tutorial on regularized partial correlation networks
Epskamp, S., & Fried, E. I. (2018) · Psychological Methods · doi:10.1037/met0000167 · Cited by 2,918
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Self-citationRobinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2020) · Psychological Medicine · doi:10.1017/s0033291719003404 · Cited by 861
On the equivalency of factor and network loadings
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Metadata
- Authors
- Haslbeck, J. M. B., & Waldorp, L. J.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2020
- Volume
- 93
- Issue
- 8
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W3019880418
- Cited by
- 746
- References
- 65
- FWCI
- 23.96
- Type
- journal article
- Language
- en
- Open access
- diamond
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