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  "Date": "2023-07-19",
  "Title": "L2 Inference for Change Points in High-Dimensional Time Series",
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  "Authors@R": "c(\nperson(\"Jiaqi\", \"Li\", email = \"lijiaqi@wustl.edu\", role = \"aut\"),\nperson(\"Likai\", \"Chen\", email = \"likai.chen@wustl.edu\", role = \"aut\"),\nperson(\"Weining\", \"Wang\", email = \"weining.wang@york.ac.uk\", role = \"aut\"),\nperson(\"Wei Biao\", \"Wu\", email = \"wbwu@galton.uchicago.edu\", role = \"aut\"),\nperson(\"Rui\", \"Lin\", email = \"ruilin1081@gmail.com\", role = \"cre\"))",
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  "Description": "Provides a method for detecting multiple change points in\nhigh-dimensional time series, targeting dense or spatially\nclustered signals. See Li et al. (2023) \"L2 Inference for\nChange Points in High-Dimensional Time Series via a Two-Way\nMOSUM\". arXiv preprint <arXiv:2208.13074>.",
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