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edecob: Event Detection Using Confidence Bounds

Detects sustained change in digital bio-marker data using simultaneous confidence bands. Accounts for noise using an auto-regressive model. Based on Buehlmann (1998) "Sieve bootstrap for smoothing in nonstationary time series" <doi:10.1214/aos/1030563978>.

Version: 1.2.2
Depends: R (≥ 3.5.0)
Imports: stats (≥ 3.5.0), ggplot2 (≥ 3.1.0), rlang (≥ 0.4.0), utils (≥ 3.5.0), graphics (≥ 3.5.0)
Suggests: survival (≥ 2.43)
Published: 2022-11-04
DOI: 10.32614/CRAN.package.edecob
Author: Zheng Chen Man [aut, cre]
Maintainer: Zheng Chen Man <zheng.chen.man at alumni.ethz.ch>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: edecob results

Documentation:

Reference manual: edecob.pdf

Downloads:

Package source: edecob_1.2.2.tar.gz
Windows binaries: r-devel: edecob_1.2.2.zip, r-release: edecob_1.2.2.zip, r-oldrel: edecob_1.2.2.zip
macOS binaries: r-release (arm64): edecob_1.2.2.tgz, r-oldrel (arm64): edecob_1.2.2.tgz, r-release (x86_64): edecob_1.2.2.tgz, r-oldrel (x86_64): edecob_1.2.2.tgz
Old sources: edecob archive

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.