Package: bgns 0.4.3

bgns: Biweight Graph and Network Statistics

Provides memory-efficient biweight midcorrelation and exact bicor-based k-nearest-neighbor graph construction for dense and sparse numeric matrices. Dense, sparse, and mixed-input paths avoid materializing full dense similarity matrices for tidy and k-nearest-neighbor workflows where possible. The implementation supports pairwise finite-overlap handling and robust correlation-based graph construction for biological expression matrices and other high-dimensional numeric data.

Authors:Aditya Kshirsagar [aut, cre]

bgns_0.4.3.tar.gz
bgns_0.4.3.zip(r-4.7-x86_64)bgns_0.4.3.zip(r-4.7-arm64)bgns_0.4.3.zip(r-4.6-x86_64)bgns_0.4.3.zip(r-4.6-arm64)bgns_0.4.3.zip(r-4.5-x86_64)
bgns_0.4.3.tgz(r-4.6-x86_64)bgns_0.4.3.tgz(r-4.6-arm64)bgns_0.4.3.tgz(r-4.5-x86_64)bgns_0.4.3.tgz(r-4.5-arm64)
bgns_0.4.3.tar.gz(r-4.7-arm64)bgns_0.4.3.tar.gz(r-4.7-x86_64)bgns_0.4.3.tar.gz(r-4.6-arm64)bgns_0.4.3.tar.gz(r-4.6-x86_64)
bgns_0.4.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bgns/json (API)

# Install 'bgns' in R:

install.packages('bgns', repos = c('https://metaddict.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/metaddict/bgns/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

openblas cpp openmp

3.70 score 2 exports 2 dependencies

Last updated from:ee7f088c03. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	146
linux-devel-x86_64	OK	158
source / vignettes	OK	213
linux-release-arm64	OK	246
linux-release-x86_64	OK	188
macos-release-arm64	OK	178
macos-release-x86_64	OK	432
macos-oldrel-arm64	OK	236
macos-oldrel-x86_64	OK	343
windows-devel-arm64	OK	334
windows-devel-x86_64	OK	153
windows-release-arm64	OK	328
windows-release-x86_64	OK	99
windows-oldrel-x86_64	OK	118
wasm-release	OK	109