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Package: r-cran-huge (1.3.5-1)

GNU R high-dimensional undirected graph estimation

Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding.

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    also a virtual package provided by libc6-udeb
  • dep: libgcc-s1 (>= 3.3.1) [not armhf]
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    dep: libgcc-s1 (>= 3.5) [armhf]
  • dep: libgomp1 (>= 4.9)
    GCC OpenMP (GOMP) support library
  • dep: libstdc++6 (>= 5.2) [armhf]
    GNU Standard C++ Library v3
    dep: libstdc++6 (>= 9) [not armhf]
  • dep: r-api-4.0
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  • dep: r-base-core (>= 4.1.1-2)
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  • dep: r-cran-igraph
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  • dep: r-cran-mass
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  • dep: r-cran-matrix
    GNU R package of classes for dense and sparse matrices
  • dep: r-cran-rcpp
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  • dep: r-cran-rcppeigen
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Architecture Package Size Installed Size Files
amd64 1,369.5 kB1561 kB [list of files]
arm64 1,365.5 kB1549 kB [list of files]
armhf 1,366.0 kB1524 kB [list of files]
ppc64el 1,388.5 kB1608 kB [list of files]