{ "_id": "6a1160c4acfb0bcc41ced715", "Package": "stepR", "Title": "Multiscale Change-Point Inference", "Version": "2.1-11", "Authors@R": "c(person(\"Pein\", \"Florian\", role = c(\"aut\", \"cre\"), email = \"f.pein@lancaster.ac.uk\"),\nperson(\"Thomas\", \"Hotz\", role = \"aut\", email = \"thomas.hotz@tu-ilmenau.de\"),\nperson(\"Hannes\", \"Sieling\", role = \"aut\", email = \"hsielin@uni-goettingen.de\"),\nperson(\"Timo\", \"Aspelmeier\", role = \"ctb\", email = \"timo.aspelmeier@mathematik.uni-goettingen.de\"))", "VignetteBuilder": "knitr", "Description": "Allows fitting of step-functions to univariate serial data\nwhere neither the number of jumps nor their positions is known\nby implementing the multiscale regression estimators SMUCE,\nsimulataneous multiscale changepoint estimator, (K. Frick, A.\nMunk and H. Sieling, 2014) and HSMUCE,\nheterogeneous SMUCE, (F. Pein, H. Sieling and A. Munk, 2017)\n. 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