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MetaCycle  

Evaluate Periodicity in Large Scale Data
View on CRAN: Click here


Download and install MetaCycle package within the R console
Install from CRAN:
install.packages("MetaCycle")

Install from Github:
library("remotes")
install_github("cran/MetaCycle")

Install by package version:
library("remotes")
install_version("MetaCycle", "1.2.0")



Attach the package and use:
library("MetaCycle")
Maintained by
Gang Wu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-12-05
Latest Update: 2019-04-18
Description:
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.
How to cite:
Gang Wu (2015). MetaCycle: Evaluate Periodicity in Large Scale Data. R package version 1.2.0, https://cran.r-project.org/web/packages/MetaCycle
Previous versions and publish date:
1.1.0 (2015-12-05 00:08)
Other packages that cited MetaCycle R package
View MetaCycle citation profile
Other R packages that MetaCycle depends, imports, suggests or enhances
Functions, R codes and Examples using the MetaCycle R package
Some associated functions: MetaCycle . cycHumanBloodData . cycHumanBloodDesign . cycMouseLiverProtein . cycMouseLiverRNA . cycSimu4h2d . cycVignettesAMP . cycYeastCycle . meta2d . meta3d . 
Some associated R codes: ARS.R . JTKv3.1p.R . LS.R . datasetsinfo.R . meta2dMainF.R . meta2dSubF.R . meta3dMainF.R . meta3dSubF.R . metaSubF.R . package.R .  Full MetaCycle package functions and examples
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