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  "Title": "Tests Based on Ordinal Patterns",
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  "Authors@R": "c(\nperson(\"Alexander\", \"Duerre\", role=c(\"aut\"), email=\"alexander.duerre@udo.edu\"),\nperson(\"Svenja\", \"Fischer\", role=c(\"ctb\"), email=\"svenja.fischer@wur.nl\"),\nperson(\"Alexander\", \"Schnurr\", role=c(\"aut\"), email=\"schnurr@mathematik.uni-siegen.de\"),\nperson(\"Angelika\", \"Silbernagel\", role=c(\"aut\",\"cre\"), email=\"silbernagel@hsu-hh.de\"))",
  "Author": "Alexander Duerre [aut], Svenja Fischer [ctb], Alexander Schnurr\n[aut], Angelika Silbernagel [aut, cre]",
  "Maintainer": "Angelika Silbernagel <silbernagel@hsu-hh.de>",
  "Description": "Ordinal patterns describe the dynamics of a time series by\nlooking at the ranks of subsequent observations. By comparing\nordinal patterns of two times series, Schnurr (2014)\n<doi:10.1007/s00362-013-0536-8> defines a robust and\nnon-parametric dependence measure: the ordinal pattern\ncoefficient. Functions to calculate this and a method to detect\na change in the pattern coefficient proposed in Schnurr and\nDehling (2017) <doi:10.1080/01621459.2016.1164706> are\nprovided. Furthermore, the package contains a function for\ncalculating the ordinal pattern frequencies. Generalized\nordinal patterns as proposed by Schnurr and Fischer (2022)\n<doi:10.1016/j.csda.2022.107472> are also considered.",
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