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.html , 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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