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fwb: Fractional Weighted Bootstrap

An implementation of the fractional weighted bootstrap to be used as a drop-in for functions in the 'boot' package. The fractional weighted bootstrap (also known as the Bayesian bootstrap) involves drawing weights randomly that are applied to the data rather than resampling units from the data. See Xu et al. (2020) <doi:10.1080/00031305.2020.1731599> for details.

Version: 0.2.0
Depends: R (≥ 3.0.0)
Imports: rlang, chk, pbapply, stats, utils, graphics
Suggests: survival, boot, sandwich (≥ 2.4-0), lmtest, parallel
Published: 2023-12-07
Author: Noah Greifer ORCID iD [aut, cre]
Maintainer: Noah Greifer <noah.greifer at gmail.com>
BugReports: https://github.com/ngreifer/fwb/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ngreifer/fwb, https://ngreifer.github.io/fwb/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: fwb results

Documentation:

Reference manual: fwb.pdf

Downloads:

Package source: fwb_0.2.0.tar.gz
Windows binaries: r-devel: fwb_0.2.0.zip, r-release: fwb_0.2.0.zip, r-oldrel: fwb_0.2.0.zip
macOS binaries: r-release (arm64): fwb_0.2.0.tgz, r-oldrel (arm64): fwb_0.2.0.tgz, r-release (x86_64): fwb_0.2.0.tgz, r-oldrel (x86_64): fwb_0.2.0.tgz
Old sources: fwb archive

Reverse dependencies:

Reverse suggests: marginaleffects, WeightIt

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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