软件包:r-cran-huge(1.3.5-2)
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.
其他与 r-cran-huge 有关的软件包
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- dep: libc6 (>= 2.29)
- GNU C 语言运行库:共享库
同时作为一个虚包由这些包填实: libc6-udeb
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- dep: libgcc-s1 (>= 3.0)
- GCC 支持库
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- dep: libgomp1 (>= 4.9)
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- dep: r-api-4.0
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- dep: r-cran-igraph
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- dep: r-cran-matrix
- GNU R package of classes for dense and sparse matrices
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- dep: r-cran-rcpp
- GNU R package for Seamless R and C++ Integration
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- dep: r-cran-rcppeigen
- GNU R package for Eigen templated linear algebra