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-4.7)eBsc_4.15.zip(r-4.6)eBsc_4.15.zip(r-4.5)
eBsc_4.15.tgz(r-4.6-x86_64)eBsc_4.15.tgz(r-4.6-arm64)eBsc_4.15.tgz(r-4.5-x86_64)eBsc_4.15.tgz(r-4.5-arm64)
eBsc_4.15.tar.gz(r-4.7-arm64)eBsc_4.15.tar.gz(r-4.7-x86_64)eBsc_4.15.tar.gz(r-4.6-arm64)eBsc_4.15.tar.gz(r-4.6-x86_64)
eBsc_4.15.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
eBsc/json (API)

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

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

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

On CRAN:

Conda:

openblascpp

2.15 score 14 scripts 350 downloads 9 exports 7 dependencies

Last updated from:c1af5e1849. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK185
linux-devel-x86_64OK150
source / vignettesOK171
linux-release-arm64OK145
linux-release-x86_64OK139
macos-release-arm64OK155
macos-release-x86_64OK250
macos-oldrel-arm64OK144
macos-oldrel-x86_64OK307
windows-develOK136
windows-releaseOK132
windows-oldrelOK166
wasm-releaseOK143

Exports:drbasisEBCparallelEBCqeBscplot.eBscprint.eBscrcpparma_innerproductrcpparma_outerproductsummary.eBsc

Dependencies:BrobdingnaglatticeMASSMatrixnlmeRcppRcppArmadillo