LPBkg: Detecting New Signals under Background Mismodelling

Given a postulated model and a set of data, the comparison density is estimated and the deviance test is implemented in order to assess if the data distribution deviates significantly from the postulated model. Finally, the results are summarized in a CD-plot as described in Algeri S. (2019) <doi:10.48550/arXiv.1906.06615>.

Version: 1.2
Depends: R (≥ 2.0.1), polynom
Imports: orthopolynom, Hmisc, grDevices, graphics, stats
Published: 2019-10-04
DOI: 10.32614/CRAN.package.LPBkg
Author: Sara Algeri, Haoran Liu
Maintainer: Sara Algeri <salgeri at umn.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: LPBkg results


Reference manual: LPBkg.pdf


Package source: LPBkg_1.2.tar.gz
Windows binaries: r-devel: LPBkg_1.2.zip, r-release: LPBkg_1.2.zip, r-oldrel: LPBkg_1.2.zip
macOS binaries: r-release (arm64): LPBkg_1.2.tgz, r-oldrel (arm64): LPBkg_1.2.tgz, r-release (x86_64): LPBkg_1.2.tgz, r-oldrel (x86_64): LPBkg_1.2.tgz
Old sources: LPBkg archive

Reverse dependencies:

Reverse imports: LPsmooth


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