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  "Package": "flex",
  "Title": "Fuzzy Linear Squares Estimation with Explicit Formula (FLEX)",
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  "Date": "2025-08-27",
  "Authors@R": "c(\nperson(given = \"Chaewon\", family = \"Lee\",\nrole = c(\"aut\", \"cre\"),\nemail = \"chaewon.lee@unc.edu\"),\nperson(given = c(\"Jin\", \"Hee\"),\nfamily = \"Yoon\",\nrole = \"ctb\")\n)",
  "Description": "The FLEX method, developed by Yoon and Choi (2013)\n<doi:10.1007/978-3-642-33042-1_21>, performs least squares\nestimation for fuzzy predictors and outcomes, generating crisp\nregression coefficients by minimizing the distance between\nobserved and predicted outcomes. It also provides functions for\nfuzzifying data and inference tasks, including significance\ntesting, fit indices, and confidence interval estimation.",
  "License": "MIT + file LICENSE",
  "BugReports": "https://github.com/cwlee-quantpsych/flex/issues",
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  "NeedsCompilation": "no",
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  "Author": "Chaewon Lee [aut, cre], Jin Hee Yoon [ctb]",
  "Maintainer": "Chaewon Lee <chaewon.lee@unc.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-09-02 06:30:07 UTC",
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    "plot",
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    {
      "page": "coefficients",
      "title": "Define generic for coefficients",
      "topics": [
        "coefficients"
      ]
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      "title": "Accessor for Coefficients",
      "topics": [
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      "title": "Compute confidence intervals for regression coefficients",
      "topics": [
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      ]
    },
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      "topics": [
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      "title": "Compute Predictions from Fuzzy Linear Model",
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      ]
    },
    {
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      "title": "Compute Residuals for Fuzzy Linear Model",
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    {
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      "title": "Compute t-values for regression coefficients",
      "topics": [
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      ]
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    {
      "page": "fuzzify_crisp_matrix",
      "title": "Fuzzify a matrix of crisp values",
      "topics": [
        "fuzzify_crisp_matrix"
      ]
    },
    {
      "page": "fuzzify_crisp_value",
      "title": "Fuzzify a single crisp value",
      "topics": [
        "fuzzify_crisp_value"
      ]
    },
    {
      "page": "fuzzify_crisp_vector",
      "title": "Fuzzify a vector of crisp values",
      "topics": [
        "fuzzify_crisp_vector"
      ]
    },
    {
      "page": "fuzzy_add",
      "title": "Add two triangular fuzzy numbers",
      "topics": [
        "fuzzy_add"
      ]
    },
    {
      "page": "fuzzy_crisp_mult",
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      "topics": [
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      ]
    },
    {
      "page": "fuzzy_d_squared",
      "title": "Compute the squared distance between two fuzzy numbers",
      "topics": [
        "fuzzy_d_squared"
      ]
    },
    {
      "page": "fuzzy_lm",
      "title": "Fuzzy Linear Regression",
      "topics": [
        "fuzzy_lm"
      ]
    },
    {
      "page": "fuzzy_mults",
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        "fuzzy_mults"
      ]
    },
    {
      "page": "plot",
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      "topics": [
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      ]
    },
    {
      "page": "plot.fuzzy_lm",
      "title": "Plot Fuzzy Regression Results",
      "topics": [
        "plot.fuzzy_lm"
      ]
    },
    {
      "page": "predictions",
      "title": "Define generic for predictions",
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        "predictions"
      ]
    },
    {
      "page": "predictions.fuzzy_lm",
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      "page": "residuals",
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      ]
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