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  "Title": "Wicked Fast, Accurate Quantiles Using t-Digests",
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  "Date": "2026-05-05",
  "Authors@R": "c(\nperson(\"Bob\", \"Rudis\", email = \"bob@rud.is\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-5670-2640\")),\nperson(\"Ted\", \"Dunning\", role = \"aut\",\ncomment = \"t-Digest algorithm; <https://github.com/tdunning/t-digest/>\"),\nperson(\"Andrew\", \"Werner\", role = \"aut\",\ncomment = \"Original C+ code; <https://github.com/ajwerner/tdigest>\")\n)",
  "Description": "The t-Digest construction algorithm, by Dunning, (2019)\n<doi:10.48550/arXiv.1902.04023>, uses a variant of\n1-dimensional k-means clustering to produce a very compact data\nstructure that allows accurate estimation of quantiles. This\nt-Digest data structure can be used to estimate quantiles,\ncompute other rank statistics or even to estimate related\nmeasures like trimmed means. The advantage of the t-Digest over\nprevious digests for this purpose is that the t-Digest handles\ndata with full floating point resolution. The accuracy of\nquantile estimates produced by t-Digests can be orders of\nmagnitude more accurate than those produced by previous digest\nalgorithms. Methods are provided to create and update t-Digests\nand retrieve quantiles from the accumulated distributions.",
  "URL": "https://git.sr.ht/~hrbrmstr/tdigest",
  "BugReports": "https://todo.sr.ht/~hrbrmstr/tdigest",
  "Copyright": "file inst/COPYRIGHTS",
  "Encoding": "UTF-8",
  "License": "MIT + file LICENSE",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.1",
  "Language": "en-US",
  "Repository": "https://hrbrmstr.r-universe.dev",
  "Date/Publication": "2026-05-05 13:40:07 UTC",
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  "NeedsCompilation": "yes",
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    "Date": "2026-06-05 06:20:13 UTC",
    "User": "root"
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  "Author": "Bob Rudis [aut, cre] (ORCID: <https://orcid.org/0000-0001-5670-2640>),\nTed Dunning [aut] (t-Digest algorithm;\n<https://github.com/tdunning/t-digest/>),\nAndrew Werner [aut] (Original C+ code;\n<https://github.com/ajwerner/tdigest>)",
  "Maintainer": "Bob Rudis <bob@rud.is>",
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    "message": "chore: clean up qmd\n",
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    "description": "🇺🇦 Pampa • Don't look at me…I do what he does—just slower. #rstats avuncular•👨‍🍳•✝️• 💤• Distinguished Engineer @ Censys + CMU Lecturer",
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      "n": 4
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    "t-digest"
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    "name": "boB Rudis",
    "description": "🇺🇦 Pampa • Don't look at me…I do what he does—just slower. #rstats avuncular•👨‍🍳•✝️• 💤• Distinguished Engineer @ Censys + CMU Lecturer"
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    "%>%",
    "as_tdigest",
    "is_tdigest",
    "td_add",
    "td_create",
    "td_merge",
    "td_quantile_of",
    "td_total_count",
    "td_value_at",
    "tdigest",
    "tquantile"
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    {
      "page": "as.list.tdigest",
      "title": "Serialize a tdigest object to an R list or unserialize a serialized tdigest list back into a tdigest object",
      "topics": [
        "as.list.tdigest",
        "as_tdigest"
      ]
    },
    {
      "page": "td_add",
      "title": "Add a value to the t-Digest with the specified count",
      "topics": [
        "td_add"
      ]
    },
    {
      "page": "td_create",
      "title": "Allocate a new histogram",
      "topics": [
        "is_tdigest",
        "td_create"
      ]
    },
    {
      "page": "td_merge",
      "title": "Merge one t-Digest into another",
      "topics": [
        "td_merge"
      ]
    },
    {
      "page": "td_quantile_of",
      "title": "Return the quantile of the value",
      "topics": [
        "td_quantile_of"
      ]
    },
    {
      "page": "td_total_count",
      "title": "Total items contained in the t-Digest",
      "topics": [
        "length.tdigest",
        "td_total_count"
      ]
    },
    {
      "page": "td_value_at",
      "title": "Return the value at the specified quantile",
      "topics": [
        "td_value_at",
        "[.tdigest"
      ]
    },
    {
      "page": "tquantile",
      "title": "Calculate sample quantiles from a t-Digest",
      "topics": [
        "quantile.tdigest",
        "tquantile"
      ]
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