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) <doi:10.48550/arXiv.1812.06948> for details.

Version: 4.17
Imports: Brobdingnag, parallel, nlme, Matrix, MASS, splines, Rcpp, mvtnorm
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-05-23
Author: Francisco Rosales, Tatyana Krivobokova, Paulo Serra.
Maintainer: Francisco Rosales <francisco.rosales-marticorena at protonmail.com>
License: GPL-2
NeedsCompilation: yes
CRAN checks: eBsc results

Documentation:

Reference manual: eBsc.pdf

Downloads:

Package source: eBsc_4.17.tar.gz
Windows binaries: r-prerel: eBsc_4.17.zip, r-release: eBsc_4.17.zip, r-oldrel: eBsc_4.17.zip
macOS binaries: r-prerel (arm64): eBsc_4.17.tgz, r-release (arm64): eBsc_4.17.tgz, r-oldrel (arm64): eBsc_4.17.tgz, r-prerel (x86_64): eBsc_4.17.tgz, r-release (x86_64): eBsc_4.17.tgz
Old sources: eBsc archive

Reverse dependencies:

Reverse depends: sephora

Linking:

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