{
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  "Package": "lqr",
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  "Title": "Robust Linear Quantile Regression",
  "Version": "5.2",
  "Date": "2024-07-12",
  "Author": "Christian E. Galarza <chedgala@espol.edu.ec>, Luis Benites\n<lbenitess@pucp.edu.pe>, Marcelo Bourguignon\n<m.p.bourguignon@gmail.com>, Victor H. Lachos\n<hlachos@uconn.edu>",
  "Maintainer": "Christian E. Galarza <cgalarza88@gmail.com>",
  "Description": "It fits a robust linear quantile regression model using a\nnew family of zero-quantile distributions for the error term.\nMissing values and censored observations can be handled as\nwell. This family of distribution includes skewed versions of\nthe Normal, Student's t, Laplace, Slash and Contaminated Normal\ndistribution. It also performs logistic quantile regression for\nbounded responses as shown in Galarza et.al.(2020)\n<doi:10.1007/s13571-020-00231-0>. It provides estimates and\nfull inference. It also provides envelopes plots for assessing\nthe fit and confidences bands when several quantiles are\nprovided simultaneously.",
  "License": "GPL (>= 2)",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-10 06:44:43 UTC",
    "User": "root"
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  "Repository": "https://chedgala.r-universe.dev",
  "Date/Publication": "2024-07-13 02:43:37 UTC",
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    "description": "Statistician by accident and christian by faith. I love travelling, teaching, eating, dancing, DJing, juggling, vibe coding, drumming, and music.",
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    "vartrunc"
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      "title": "Australian institute of sport data",
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        "RCC",
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        "Ferr",
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        "Label",
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      "title": "Tumor-cell resistance to death",
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      "title": "Robust Linear Quantile Regression",
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      "topics": [
        "ais"
      ]
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      "page": "best.lqr",
      "title": "Best Fit in Robust Linear Quantile Regression",
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        "best.lqr"
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      "title": "Skew-t quantile regression for censored and missing data",
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      "title": "Truncated Distributions",
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        "extrunc",
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        "rtrunc",
        "vartrunc"
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      "page": "lqr",
      "title": "Robust Linear Quantile Regression",
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