{
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  "Title": "Constrained Regression Model for an Ordinal Response and Ordinal\nPredictors",
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  "Author": "Javier Espinosa <javier.espinosa.b@usach.cl>",
  "Maintainer": "Javier Espinosa <javier.espinosa.b@usach.cl>",
  "Description": "Fits a constrained regression model for an ordinal\nresponse with ordinal predictors and possibly others, Espinosa\nand Hennig (2019) <DOI:10.1007/s11222-018-9842-2>. The\nparameter estimates associated with an ordinal predictor are\nconstrained to be monotonic. If a monotonicity direction\n(isotonic or antitonic) is not specified for an ordinal\npredictor by the user, then one of the available methods will\neither establish it or drop the monotonicity assumption. Two\nmonotonicity tests are also available to test the null\nhypothesis of monotonicity over a set of parameters associated\nwith an ordinal predictor.",
  "License": "GPL-2",
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  "Date/Publication": "2023-08-25 15:30:55 UTC",
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    "extra/citation.json",
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    "monoTestConfReg",
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      "title": "Real data example",
      "object": "realDataExample",
      "class": [
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      "fields": [
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        "EduLevel",
        "Age",
        "IncQuint",
        "Gender",
        "Health"
      ],
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      "page": "confRegCCR",
      "title": "Parameter Vector in Confidence Region CCR",
      "topics": [
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      "page": "confRegUCRandUCCR",
      "title": "Parameter Vector in Confidence Regions UCR and/or UCCR",
      "topics": [
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      "title": "Real data example",
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    },
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      "page": "mdcp",
      "title": "Monotonicity Direction Classification (MDC) procedure",
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      "title": "Monotonicity test",
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