{
  "_id": "6a1018d3acfb0bcc41c85b4d",
  "Package": "JQL",
  "Type": "Package",
  "Title": "Jump Q-Learning for Individualized Interval-Valued Dose Rule",
  "Version": "3.6.9",
  "Author": "Hengrui Cai <hcai5@ncsu.edu>, Chengchun shi <cshi4@ncsu.edu>,\nRui Song <rsong@ncsu.edu>, Wenbin Lu <wlu4@ncsu.edu>",
  "Maintainer": "Hengrui Cai <hcai5@ncsu.edu>",
  "Description": "We provide tools to estimate the individualized\ninterval-valued dose rule (I2DR) that maximizes the expected\nbeneficial clinical outcome for each individual and returns an\noptimal interval-valued dose, by using the jump Q-learning\n(JQL) method. The jump Q-learning method directly models the\nconditional mean of the response given the dose level and the\nbaseline covariates via jump penalized least squares regression\nunder the framework of Q learning. We develop a searching\nalgorithm by dynamic programming in order to find the optimal\nI2DR with the time complexity O(n2) and spatial complexity\nO(n). To alleviate the effects of misspecification of the\nQ-function, a residual jump Q-learning is further proposed to\nestimate the optimal I2DR. The outcome of interest includes the\nbest partition of the entire dosage of interest, the regression\ncoefficients of each partition, and the value function under\nthe estimated I2DR as well as the Wald-type confidence interval\nof value function constructed through the Bootstrap.",
  "License": "LGPL-3",
  "Encoding": "UTF-8",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-14 19:39:20 UTC",
    "User": "root"
  },
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://cranhaven.r-universe.dev",
  "Date/Publication": "2026-05-14 12:02:00 UTC",
  "RemoteUrl": "https://github.com/cranhaven/cranhaven.r-universe.dev",
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  "_published": "2026-05-22T08:50:27.151Z",
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  "_buildurl": "https://github.com/r-universe/cranhaven/actions/runs/25881259379",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cranhaven/cranhaven.r-universe.dev",
  "_commit": {
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    "author": "GitHub Action <action@github.com>",
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    "email": "hcai5@ncsu.edu",
    "login": "anoce-cvae",
    "uuid": 63676756
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  "_registered": true,
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  "_owner": "cranhaven",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-20",
      "n": 1
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  "_tags": [],
  "_topics": [
    "archived",
    "packages",
    "r-universe"
  ],
  "_stars": 5,
  "_contributors": [
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      "user": "henrikbengtsson",
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    "type": "organization",
    "name": "cranhaven",
    "description": "CRANhaven - Repository for Recently Archived CRAN Packages"
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  "_downloads": {
    "count": 163,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/JQL"
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  "_mentions": 2,
  "_devurl": "https://github.com/cranhaven/cranhaven.r-universe.dev",
  "_searchresults": 2,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
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    "manual.pdf"
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  "_realowner": "anoce-cvae",
  "_cranurl": false,
  "_releases": [
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      "date": "2019-02-22"
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    "opt.dose",
    "tune.JQL",
    "tune.RJQL"
  ],
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    {
      "page": "find.I2DR",
      "title": "Estimating the Individualized Interval-valued Dose Rule via (Residual) Jump Q-learning.",
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      ]
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      "title": "Optimal Interval-valued Dose under the Individualized Interval-valued Dose Rule via (Residual) Jump Q-learning.",
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    },
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    },
    {
      "page": "tune.RJQL",
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