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  "Title": "Top-Down Time Ratio Segmentation for Coordinate Trajectories",
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  "Authors@R": "person(\"Danielle\", \"McCool\", email = \"d.m.mccool@uu.nl\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-7055-7539\"))",
  "Description": "Data collected on movement behavior is often in the form\nof time- stamped latitude/longitude coordinates sampled from\nthe underlying movement behavior. These data can be compressed\ninto a set of segments via the Top- Down Time Ratio\nSegmentation method described in Meratnia and de By (2004)\n<doi:10.1007/978-3-540-24741-8_44> which, with some loss of\ninformation, can both reduce the size of the data as well as\nprovide corrective smoothing mechanisms to help reduce the\nimpact of measurement error.  This is an improvement on the\nwell-known Douglas-Peucker algorithm for segmentation that\noperates not on the basis of perpendicular distances. Top-Down\nTime Ratio segmentation allows for disparate sampling time\nintervals by calculating the distance between locations and\nsegments with respect to time. Provided a trajectory with\ntimestamps, tdtr() returns a set of straight- line segments\nthat can represent the full trajectory. McCool, Lugtig, and\nSchouten (2022) <doi:10.1007/s11116-022-10328-2> describe this\nmethod as implemented here in more detail.",
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  "Repository": "https://daniellemccool.r-universe.dev",
  "Date/Publication": "2022-09-22 08:57:42 UTC",
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      "title": "Split the difference when it comes to difftimes",
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      "title": "Perform Top-Down Time Ratio segmentation",
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