Package: eBsc 4.17

Francisco Rosales

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_4.17.tar.gz
eBsc_4.17.tar.gz(r-4.5-noble)eBsc_4.17.tar.gz(r-4.4-noble)
eBsc_4.17.tgz(r-4.4-emscripten)eBsc_4.17.tgz(r-4.3-emscripten)
eBsc.pdf |eBsc.html
eBsc/json (API)

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

Peer review:

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

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.59 score 1 packages 13 scripts 239 downloads 9 exports 8 dependencies

Last updated 1 years agofrom:bb5decbc9b. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 13 2024
R-4.5-linux-x86_64OKOct 13 2024

Exports:drbasisEBCparallelEBCqeBscplot.eBscprint.eBscrcpparma_innerproductrcpparma_outerproductsummary.eBsc

Dependencies:BrobdingnaglatticeMASSMatrixmvtnormnlmeRcppRcppArmadillo