Package: hdbcp 1.0.0

JaeHoon Kim

hdbcp: Bayesian Change Point Detection for High-Dimensional Data

Functions implementing change point detection methods using the maximum pairwise Bayes factor approach. Additionally, the package includes tools for generating simulated datasets for comparing and evaluating change point detection techniques.

Authors:JaeHoon Kim [aut, cre], KyoungJae Lee [aut, ths]

hdbcp_1.0.0.tar.gz
hdbcp_1.0.0.zip(r-4.7-x86_64)hdbcp_1.0.0.zip(r-4.7-arm64)hdbcp_1.0.0.zip(r-4.6-x86_64)hdbcp_1.0.0.zip(r-4.6-arm64)hdbcp_1.0.0.zip(r-4.5-x86_64)
hdbcp_1.0.0.tgz(r-4.6-x86_64)hdbcp_1.0.0.tgz(r-4.6-arm64)hdbcp_1.0.0.tgz(r-4.5-x86_64)hdbcp_1.0.0.tgz(r-4.5-arm64)
hdbcp_1.0.0.tar.gz(r-4.7-arm64)hdbcp_1.0.0.tar.gz(r-4.7-x86_64)hdbcp_1.0.0.tar.gz(r-4.6-arm64)hdbcp_1.0.0.tar.gz(r-4.6-x86_64)
hdbcp_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hdbcp/json (API)

# Install 'hdbcp' in R:
install.packages('hdbcp', repos = c('https://jaehoonkim98.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jaehoonkim98/hdbcp/issues

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

On CRAN:

Conda:

openblascppopenmp

2.70 score 394 downloads 7 exports 17 dependencies

Last updated from:f3df4e7cd3. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK139
linux-devel-x86_64OK124
source / vignettesOK195
linux-release-arm64OK92
linux-release-x86_64OK165
macos-release-arm64OK216
macos-release-x86_64OK342
macos-oldrel-arm64OK201
macos-oldrel-x86_64OK350
windows-devel-arm64OK363
windows-devel-x86_64OK148
windows-release-arm64OK372
windows-release-x86_64OK113
windows-oldrel-x86_64OK112
wasm-releaseOK108

Exports:generate_cov_datasetsgenerate_mean_datasetsmajority_rule_mxPBFmvrnorm_cppmxPBF_combinedmxPBF_covmxPBF_mean

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6RcppRcppArmadillorlangtibbletidyselectutf8vctrswithr