MetaCycle: Evaluate Periodicity in Large Scale Data

There are two functions-meta2d and meta3d for detecting rhythmic signals from time-series datasets. For analyzing time-series datasets without individual information, 'meta2d' is suggested, which could incorporates multiple methods from ARSER, JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For analyzing time-series datasets with individual information, 'meta3d' is suggested, which takes use of any one of these three methods to analyze time-series data individual by individual and gives out integrated values based on analysis result of each individual.

Version:	1.2.0
Depends:	R (≥ 3.0.2)
Imports:	gnm
Suggests:	knitr, rmarkdown, parallel
Published:	2019-04-18
Author:	Gang Wu [aut, cre], Ron Anafi [aut, ctb], John Hogenesch [aut, ctb], Michael Hughes [aut, ctb], Karl Kornacker [aut, ctb], Xavier Li [aut, ctb], Matthew Carlucci [aut, ctb]
Maintainer:	Gang Wu <wggucas at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	MetaCycle results

Documentation:

Reference manual:	MetaCycle.pdf
Vignettes:	Introduction to MetaCycle

Downloads:

Package source:	MetaCycle_1.2.0.tar.gz
Windows binaries:	r-devel: MetaCycle_1.2.0.zip, r-release: MetaCycle_1.2.0.zip, r-oldrel: MetaCycle_1.2.0.zip
macOS binaries:	r-release (arm64): MetaCycle_1.2.0.tgz, r-oldrel (arm64): MetaCycle_1.2.0.tgz, r-release (x86_64): MetaCycle_1.2.0.tgz, r-oldrel (x86_64): MetaCycle_1.2.0.tgz
Old sources:	MetaCycle archive

Reverse dependencies:

Reverse imports:

DiscoRhythm

Linking:

Please use the canonical form https://CRAN.R-project.org/package=MetaCycle to link to this page.