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peperr: Parallelised Estimation of Prediction Error

Designed for prediction error estimation through resampling techniques, possibly accelerated by parallel execution on a compute cluster. Newly developed model fitting routines can be easily incorporated. Methods used in the package are detailed in Porzelius Ch., Binder H. and Schumacher M. (2009) <doi:10.1093/bioinformatics/btp062> and were used, for instance, in Porzelius Ch., Schumacher M.and Binder H. (2011) <doi:10.1007/s00180-011-0236-6>.

Version: 1.5
Depends: snowfall, survival, methods
Suggests: locfit, penalized, codetools
Published: 2023-03-22
DOI: 10.32614/CRAN.package.peperr
Author: Christine Porzelius, Harald Binder
Maintainer: Frederic Bertrand <frederic.bertrand at utt.fr>
BugReports: https://github.com/fbertran/peperr/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/fbertran/peperr/, https://fbertran.github.io/peperr/
NeedsCompilation: yes
Materials: README NEWS
In views: HighPerformanceComputing, Survival
CRAN checks: peperr results

Documentation:

Reference manual: peperr.pdf

Downloads:

Package source: peperr_1.5.tar.gz
Windows binaries: r-devel: peperr_1.5.zip, r-release: peperr_1.5.zip, r-oldrel: peperr_1.5.zip
macOS binaries: r-release (arm64): peperr_1.5.tgz, r-oldrel (arm64): peperr_1.5.tgz, r-release (x86_64): peperr_1.5.tgz, r-oldrel (x86_64): peperr_1.5.tgz
Old sources: peperr archive

Reverse dependencies:

Reverse imports: c060

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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