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Provides functionality for estimating cross-sectional network structures representing partial correlations in R, while accounting for missing values in the data. Networks are estimated via neighborhood selection, i.e., node-wise multiple regression, with model selection guided by information criteria. Missing data can be handled primarily via multiple imputation or a maximum likelihood-based approach; deletion techniques are available but secondary <doi:10.31234/osf.io/qpj35>.
Package details |
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Author | Kai Jannik Nehler [aut, cre] (ORCID: <https://orcid.org/0000-0003-3764-761X>) |
Maintainer | Kai Jannik Nehler <nehler@psych.uni-frankfurt.de> |
License | GPL (>= 3) |
Version | 0.1.0 |
Package repository | View on CRAN |
Installation |
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