Package: baggingbwsel 1.1

baggingbwsel: Bagging Bandwidth Selection in Kernel Density and Regression Estimation

Bagging bandwidth selection methods for the Parzen-Rosenblatt and Nadaraya-Watson estimators. These bandwidth selectors can achieve greater statistical precision than their non-bagged counterparts while being computationally fast. See Barreiro-Ures et al. (2020) <doi:10.1093/biomet/asaa092> and Barreiro-Ures et al. (2021) <doi:10.48550/arXiv.2105.04134>.

Authors:Daniel Barreiro-Ures [aut], Ruben Fernandez-Casal [aut, cre], Jeffrey Hart [aut], Ricardo Cao [aut], Mario Francisco-Fernandez [aut]

baggingbwsel_1.1.tar.gz
baggingbwsel_1.1.zip(r-4.7)baggingbwsel_1.1.zip(r-4.6)baggingbwsel_1.1.zip(r-4.5)
baggingbwsel_1.1.tgz(r-4.6-x86_64)baggingbwsel_1.1.tgz(r-4.6-arm64)baggingbwsel_1.1.tgz(r-4.5-x86_64)baggingbwsel_1.1.tgz(r-4.5-arm64)
baggingbwsel_1.1.tar.gz(r-4.7-arm64)baggingbwsel_1.1.tar.gz(r-4.7-x86_64)baggingbwsel_1.1.tar.gz(r-4.6-arm64)baggingbwsel_1.1.tar.gz(r-4.6-x86_64)
baggingbwsel_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
baggingbwsel/json (API)

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

Bug tracker:https://github.com/rubenfcasal/baggingbwsel/issues

Pkgdown/docs site:https://rubenfcasal.github.io

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

On CRAN:

Conda:

cpp

2.70 score 209 downloads 6 exports 10 dependencies

Last updated from:02f1eb8248. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK123
linux-devel-x86_64OK126
source / vignettesOK182
linux-release-arm64OK136
linux-release-x86_64OK136
macos-release-arm64OK87
macos-release-x86_64OK199
macos-oldrel-arm64OK125
macos-oldrel-x86_64OK198
windows-develOK125
windows-releaseOK105
windows-oldrelOK103
wasm-releaseOK158

Exports:bagcvbagreghboot_baghsss_densmopttss_dens

Dependencies:codetoolsdoParallelforeachiteratorskeddmclustmisc3dnor1mixRcppsm