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wbsts
View on CRAN: Click
here
Download and install wbsts package within the R console
Install from CRAN:
install.packages("wbsts")
Install from Github:
library("remotes")
install_github("cran/wbsts")
Install by package version:
library("remotes")
install_version("wbsts", "2.1")
Attach the package and use:
library("wbsts")
Maintained by
Karolos Korkas
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-08-23
Latest Update: 2020-06-12
Description:
Implements detection for the number and locations of the change-points in a time series using the Wild Binary Segmentation and the Locally Stationary Wavelet model of Korkas and Fryzlewicz (2017) <doi:10.5705/ss.202015.0262>.
How to cite:
Karolos Korkas (2015). wbsts: Multiple Change-Point Detection for Nonstationary Time Series. R package version 2.1, https://cran.r-project.org/web/packages/wbsts
Previous versions and publish date:
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Other R packages that wbsts depends,
imports, suggests or enhances
Functions, R codes and Examples using
the wbsts R package
Some associated functions: across_fip . cr.rand.max.inner.prod . cusum . ews.trans . finner_prod_maxp . get.thres.ar . get.thres . hello . multi_across_fip . post.processing . sim.pw.ar . sim.pw.ar2 . sim.pw.arma . tau.fun . uh.wbs . wbs.lsw . wbsts-package .
Some associated R codes: RcppExports.R . cr.rand.max.inner.prod.R . ews.trans.R . get.thres.R . get.thres.ar.R . hello.R . post.processing.R . sim.pw.ar.R . sim.pw.ar2.R . sim.pw.arma.R . tau.fun.R . uh.wbs.R . wbs.lsw.R . Full wbsts package functions and examples
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