{ "_id": "6a180e21acfb0bcc41dae154", "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 ", "Maintainer": "Zhibing He ", "Description": "Simultaneously detect the number and locations of change\npoints in piecewise linear models under stationary Gaussian\nnoise allowing autocorrelated random noise. The core idea is to\ntransform the problem of detecting change points into the\ndetection of local extrema (local maxima and local\nminima)through kernel smoothing and differentiation of the data\nsequence, see Cheng et al. (2020) . A\nlow-computational and fast algorithm call 'dSTEM' is introduced\nto detect change points based on the 'STEM' algorithm in D.\nCheng and A. Schwartzman (2017) .", "URL": "https://doi.org/10.1214/20-EJS1751,\nhttps://doi.org/10.1214/16-AOS1458", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-28 09:40:35 UTC", "User": "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", "MD5sum": "8a3279678e10879f891bd44910e3a9ef", "_user": "cran", "_type": "src", "_file": "dSTEM_2.0-1.tar.gz", "_fileid": "79509fdebad7ece899dbc1f116a21267aef4e165d0e298ef09a88ce512d7ace9", "_filesize": 175875, "_sha256": "79509fdebad7ece899dbc1f116a21267aef4e165d0e298ef09a88ce512d7ace9", "_created": "2026-05-28T09:40:35.000Z", "_published": "2026-05-28T09:42:57.288Z", "_distro": "noble", "_jobs": [ { "job": 78264406964, "time": 100, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", 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"Volume", "Open", "High", "Low" ], "rows": 2517, "table": true, "tojson": true } ], "_help": [ { "page": "conv", "title": "Compute convolution function using FFT", "topics": [ "conv" ] }, { "page": "cp.plt", "title": "Plot data sequence, the first and second-order derivatives, and their local extrema", "topics": [ "cp.plt" ] }, { "page": "cpTest", "title": "Multiple testing of change points for kernel smoothed data", "topics": [ "cpTest" ] }, { "page": "dstem", "title": "Detection of change points based on 'dSTEM' algorithm", "topics": [ "dstem" ] }, { "page": "est.pair", "title": "Identify pairwise local maxima and local minima of the second-order derivative", "topics": [ "est.pair" ] }, { "page": "est.sigma2", "title": "Estimate variance of smoothed Gaussian noise", "topics": [ "est.sigma2" ] }, { "page": "est.slope", "title": "Estimate piecewise slope for piecewise linear model", "topics": [ "est.slope" ] }, { "page": "Fdr", "title": "Compute TPR and FPR", "topics": [ "Fdr" ] }, { 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