Package: dSTEM
Type: Package
Title: Multiple Testing of Local Extrema for Detection of Change Points
Version: 2.0-1
Date: 2023-6-20
Author: Zhibing He <zhibingh@asu.edu>
Maintainer: Zhibing He <zhibingh@asu.edu>
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) <doi:10.1214/20-EJS1751>. 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) <doi:10.1214/16-AOS1458>.
Depends: R (>= 3.1.0)
Imports: MASS
URL: https://doi.org/10.1214/20-EJS1751,
        https://doi.org/10.1214/16-AOS1458
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
NeedsCompilation: no
Packaged: 2026-09-24 07:54:37 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2023-06-21 08:00:07 UTC
RemoteUrl: https://github.com/cran/dSTEM
RemoteRef: HEAD
RemoteSha: aaab118e5637f50b7f9da70f4074f28d87d73a1f
Built: R 4.6.0; ; 2026-09-24 07:56:46 UTC; unix
