Package: eBsc 4.15

eBsc: "Empirical Bayes Smoothing Splines with Correlated Errors"

Presents a statistical method that uses a recursive algorithm for signal extraction. The method handles a non-parametric estimation for the correlation of the errors. See "Krivobokova", "Serra", "Rosales" and "Klockmann" (2021) <arxiv:1812.06948> for details.

Authors:Francisco Rosales, Tatyana Krivobokova, Paulo Serra.

eBsc_4.15.tar.gz
eBsc_4.15.zip(r-4.5)eBsc_4.15.zip(r-4.4)eBsc_4.15.zip(r-4.3)
eBsc_4.15.tgz(r-4.4-x86_64)eBsc_4.15.tgz(r-4.4-arm64)eBsc_4.15.tgz(r-4.3-x86_64)eBsc_4.15.tgz(r-4.3-arm64)
eBsc_4.15.tar.gz(r-4.5-noble)eBsc_4.15.tar.gz(r-4.4-noble)
eBsc_4.15.tgz(r-4.4-emscripten)eBsc_4.15.tgz(r-4.3-emscripten)
eBsc.pdf |eBsc.html✨
eBsc/json (API)

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

Peer review:

Bug tracker:https://github.com/lfrm/ebsc-r-package/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

2.59 score 1 packages 13 scripts 233 downloads 9 exports 7 dependencies

Last updated 2 years agofrom:c1af5e1849. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-win-x86_64OKNov 07 2024
R-4.5-linux-x86_64OKNov 07 2024
R-4.4-win-x86_64OKNov 07 2024
R-4.4-mac-x86_64OKNov 07 2024
R-4.4-mac-aarch64OKNov 07 2024
R-4.3-win-x86_64OKNov 07 2024
R-4.3-mac-x86_64OKNov 07 2024
R-4.3-mac-aarch64OKNov 07 2024

Exports:drbasisEBCparallelEBCqeBscplot.eBscprint.eBscrcpparma_innerproductrcpparma_outerproductsummary.eBsc

Dependencies:BrobdingnaglatticeMASSMatrixnlmeRcppRcppArmadillo