{ "_id": "6a1ed2dcb401979e7340df90", "Package": "not", "Type": "Package", "Title": "Narrowest-Over-Threshold Change-Point Detection", "Version": "1.6", "Date": "2024-09-23", "Authors@R": "c(person(given = \"Rafal\", family = \"Baranowski\", role = \"aut\"),\nperson(given = \"Yining\", family = \"Chen\", role = c(\"aut\", \"cre\"), email = \"y.chen101@lse.ac.uk\"),\nperson(given = \"Piotr\", family = \"Fryzlewicz\", role = \"aut\"))", "Description": "Provides efficient implementation of the\nNarrowest-Over-Threshold methodology for detecting an unknown\nnumber of change-points occurring at unknown locations in\none-dimensional data following 'deterministic signal + noise'\nmodel. Currently implemented scenarios are: piecewise-constant\nsignal, piecewise-constant signal with a heavy-tailed noise,\npiecewise-linear signal, piecewise-quadratic signal,\npiecewise-constant signal and with piecewise-constant variance\nof the noise. 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