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dSTEM  

Multiple Testing of Local Extrema for Detection of Change Points
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("dSTEM", "2.0-1")



Attach the package and use:
library("dSTEM")
Maintained by
Zhibing He
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-21
Latest Update: 2023-06-21
Description:
Simultaneously detect the number and locations of change points in piecewise linear models under stationary Gaussian noise allowing autocorrelated random noise. The core idea is to transform the problem of detecting change points into the detection of local extrema (local maxima and local minima)through kernel smoothing and differentiation of the data sequence, see Cheng et al. (2020) . A low-computational and fast algorithm call 'dSTEM' is introduced to detect change points based on the 'STEM' algorithm in D. Cheng and A. Schwartzman (2017) .
How to cite:
Zhibing He (2023). dSTEM: Multiple Testing of Local Extrema for Detection of Change Points. R package version 2.0-1, https://cran.r-project.org/web/packages/dSTEM. Accessed 18 Sep. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited dSTEM R package
View dSTEM citation profile
Other R packages that dSTEM depends, imports, suggests or enhances
Complete documentation for dSTEM
Functions, R codes and Examples using the dSTEM R package
Some associated functions: Fdr . HST_stock . conv . cp.plt . cpTest . dstem . est.pair . est.sigma2 . est.slope . fdrBH . gen.signal . smth.gau . snr . which.peaks . 
Some associated R codes: conv.R . data.R . fdrBH.R . main.R . whichPeaks.R .  Full dSTEM package functions and examples
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