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.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✨
card.svg |card.png
hdbcp/json (API)

# Install 'hdbcp' in R:
install.packages('hdbcp', repos = c('https://cran.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

1.70 score 4 scripts 539 downloads 7 exports 17 dependencies

Last updated from:11106cfd10. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK148
linux-devel-x86_64OK120
source / vignettesOK168
linux-release-arm64OK137
linux-release-x86_64OK121
wasm-releaseOK111

Exports:generate_cov_datasetsgenerate_mean_datasetsmajority_rule_mxPBFmvrnorm_cppmxPBF_combinedmxPBF_covmxPBF_mean

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6RcppRcppArmadillorlangtibbletidyselectutf8vctrswithr