r-cran-huge 1.3.4.1-1build1 source package in Ubuntu
Changelog
r-cran-huge (1.3.4.1-1build1) groovy; urgency=medium * No-change rebuild against r-api-4.0 -- Graham Inggs <email address hidden> Sat, 30 May 2020 19:24:18 +0000
Upload details
- Uploaded by:
- Graham Inggs
- Uploaded to:
- Groovy
- Original maintainer:
- Debian R Packages Maintainers
- Architectures:
- any
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| r-cran-huge_1.3.4.1.orig.tar.gz | 1.9 MiB | 78ef9eae464d52c5247998b9514a81b178419b857b1a6c00d885e3ae6c03a886 |
| r-cran-huge_1.3.4.1-1build1.debian.tar.xz | 2.7 KiB | 89b4f00cdc7b520304b3f07e459b6096ace360fa6f10b6e950802e9f96a33809 |
| r-cran-huge_1.3.4.1-1build1.dsc | 2.1 KiB | b24a9c73d80d264ae4d47ccd8b1db38ca920522a40c72912630a7fc74853d396 |
Available diffs
Binary packages built by this source
- r-cran-huge: 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.
- r-cran-huge-dbgsym: debug symbols for r-cran-huge
