{
  "_id": "6ad13b5cd3c80a766859b9b4",
  "Package": "fuzzySurvival",
  "Title": "Fuzzy Survival Analysis with Vague Event Times and Fuzzy\nCensoring",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(given = \"Mukul\", family = \"Bijalwan\", role = c(\"aut\", \"cre\"),\nemail = \"mukulbijalwan555@gmail.com\",\ncomment = c(ORCID = \"0009-0001-3040-6912\")),\nperson(given = \"Gunjan\", family = \"Aggrwal\", role = \"aut\"),\nperson(given = \"Mukul\", family = \"Jain\", role = \"aut\"))",
  "Description": "Fuzzy survival analysis for data in which event times\nand/or failure indicators are vague, for instance when a\nfailure is only known to have occurred during the second\nquarter of a year, or when it is uncertain whether a subject\nlost to follow-up had in fact failed.  Vague information is\nrepresented by fuzzy numbers.  The package provides a fuzzy\nproduct-limit estimator obtained from nested alpha-cuts of the\nfuzzy survival function, a fuzzy Cox proportional hazards model\nwith fuzzy coefficient and hazard ratio estimates, and a fuzzy\nlog-rank test. Type-reduction utilities for summarizing fuzzy\nestimates by single numbers, a simulation engine for validation\nstudies, plotting, print and summary methods, and alpha-cut\nbased confidence bands are provided.  The bounds are computed\nat the alpha-cuts of the fuzzy event times, so the alpha-cut\nintervals returned for the survival function, the regression\ncoefficients and the test statistic are nested by construction.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "Packaged": {
    "Date": "2026-10-15 20:42:24 UTC",
    "User": "root"
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  "Author": "Mukul Bijalwan [aut, cre] (ORCID:\n<https://orcid.org/0009-0001-3040-6912>), Gunjan Aggrwal [aut],\nMukul Jain [aut]",
  "Maintainer": "Mukul Bijalwan <mukulbijalwan555@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-10-15 19:16:57 UTC",
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    "author": "Mukul Bijalwan <mukulbijalwan555@gmail.com>",
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    "description": "Research Scholar - Statistics",
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  "_exports": [
    "alpha_cuts",
    "as_crisp",
    "as_fuzzy_number",
    "core",
    "defuzz",
    "defuzz.fcox",
    "defuzz.fkm",
    "fcox",
    "fkm",
    "fkm_fuzzy_surv",
    "flogrank",
    "fuzzy_number_crisp",
    "fuzzy_number_from_acut",
    "fuzzy_number_interval",
    "fuzzy_number_trapezoid",
    "fuzzy_number_triangle",
    "fuzzy_spread",
    "fuzzy_surv",
    "is_crisp",
    "is_fuzzy_number",
    "is.fuzzy_number",
    "membership",
    "sim_fuzzy_surv",
    "support"
  ],
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    {
      "name": "fuzzy_dfs",
      "title": "Simulated disease-free survival with vague event times",
      "object": "fuzzy_dfs",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "age",
        "arm",
        "sex",
        "ft",
        "fs",
        "true_time",
        "true_status",
        "observed"
      ],
      "rows": 240,
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      "tojson": false
    }
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    {
      "page": "alpha_cuts",
      "title": "Alpha-cuts, support, core and membership of fuzzy numbers",
      "topics": [
        "alpha_cuts",
        "core",
        "membership",
        "support"
      ]
    },
    {
      "page": "as_crisp",
      "title": "Crisp representatives of fuzzy numbers",
      "topics": [
        "as_crisp"
      ]
    },
    {
      "page": "as_fuzzy_number",
      "title": "Coerce to a 'fuzzy_number', unwrapping data frame columns",
      "topics": [
        "as_fuzzy_number"
      ]
    },
    {
      "page": "c.fuzzy_number",
      "title": "Combine fuzzy numbers",
      "topics": [
        "c.fuzzy_number"
      ]
    },
    {
      "page": "defuzz",
      "title": "Defuzzification of fuzzy numbers",
      "topics": [
        "defuzz"
      ]
    },
    {
      "page": "defuzz.fcox",
      "title": "Defuzzification of fuzzy Cox coefficients",
      "topics": [
        "defuzz.fcox"
      ]
    },
    {
      "page": "defuzz.fkm",
      "title": "Defuzzification of an 'fkm' fit",
      "topics": [
        "defuzz.fkm"
      ]
    },
    {
      "page": "exp.fuzzy_number",
      "title": "Exponential of a fuzzy number",
      "topics": [
        "exp.fuzzy_number"
      ]
    },
    {
      "page": "fcox",
      "title": "Fuzzy Cox proportional hazards model",
      "topics": [
        "fcox",
        "fcox.default",
        "fcox.formula"
      ]
    },
    {
      "page": "fkm",
      "title": "Fuzzy Kaplan-Meier estimator",
      "topics": [
        "fkm",
        "fkm.default",
        "fkm.formula"
      ]
    },
    {
      "page": "fkm_fuzzy_surv",
      "title": "Fuzzy survival curve as fuzzy numbers",
      "topics": [
        "fkm_fuzzy_surv"
      ]
    },
    {
      "page": "flogrank",
      "title": "Fuzzy log-rank test for a difference between two groups",
      "topics": [
        "flogrank"
      ]
    },
    {
      "page": "fuzzy_dfs",
      "title": "Simulated disease-free survival with vague event times",
      "topics": [
        "fuzzy_dfs"
      ]
    },
    {
      "page": "fuzzy_number",
      "title": "Vague (fuzzy) quantities on the real line",
      "topics": [
        "fuzzy_number",
        "fuzzy_number_crisp",
        "fuzzy_number_from_acut",
        "fuzzy_number_interval",
        "fuzzy_number_trapezoid",
        "fuzzy_number_triangle"
      ]
    },
    {
      "page": "fuzzy_spread",
      "title": "Width (diffusion) of fuzzy numbers",
      "topics": [
        "fuzzy_spread"
      ]
    },
    {
      "page": "fuzzy_surv",
      "title": "Survival data with vague times or vague failure indicators",
      "topics": [
        "fuzzy_surv"
      ]
    },
    {
      "page": "fuzzy-arith",
      "title": "Arithmetic on fuzzy numbers",
      "topics": [
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        "Ops.fuzzy_number"
      ]
    },
    {
      "page": "is_crisp",
      "title": "Is a fuzzy number crisp?",
      "topics": [
        "is_crisp"
      ]
    },
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      "title": "Test whether an object is a fuzzy number",
      "topics": [
        "is.fuzzy_number",
        "is_fuzzy_number"
      ]
    },
    {
      "page": "plot.fkm",
      "title": "Plot fuzzy Kaplan-Meier curves",
      "topics": [
        "plot.fkm"
      ]
    },
    {
      "page": "plot.fuzzy_number",
      "title": "Plot the membership function of fuzzy numbers",
      "topics": [
        "plot.fuzzy_number"
      ]
    },
    {
      "page": "sim_fuzzy_surv",
      "title": "Simulate survival data with vague event times and vague indicators",
      "topics": [
        "sim_fuzzy_surv"
      ]
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      "page": "summary.fcox",
      "title": "Summaries and plots of a fuzzy Cox fit",
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        "plot.fcox",
        "print.fcox",
        "summary.fcox"
      ]
    },
    {
      "page": "summary.fkm",
      "title": "Summaries of a fuzzy Kaplan-Meier fit",
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        "summary.fkm"
      ]
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    "survival"
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      "title": "Fuzzy survival analysis with vague event times",
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      "headings": [
        "Why fuzzy survival analysis?",
        "1 Representing vague information",
        "2 The data container",
        "3 The fuzzy Kaplan–Meier estimator",
        "4 Comparing two arms",
        "5 The fuzzy Cox model",
        "6 Reducing a fuzzy number to a number",
        "7 What the fuzzy bounds do and do not mean",
        "8 Validating your own setting",
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        "The guaranteed properties"
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