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  "Title": "Estimate a Log-Concave Probability Mass Function from Discrete\nI.i.d. Observations",
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  "Date": "2026-04-26",
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  "Description": "Given independent and identically distributed observations\nX(1), ..., X(n), allows to compute the maximum likelihood\nestimator (MLE) of probability mass function (pmf) under the\nassumption that it is log-concave, see Weyermann (2007) and\nBalabdaoui, Jankowski, Rufibach, and Pavlides (2012). The main\nfunctions of the package are 'logConDiscrMLE' that allows\ncomputation of the log-concave MLE, 'logConDiscrCI' that\ncomputes pointwise confidence bands for the MLE, and\n'kInflatedLogConDiscr' that computes a mixture of a log-concave\nPMF and a point mass at k.",
  "License": "GPL (>= 2)",
  "URL": "http://www.kasparrufibach.ch ,\nhttps://people.math.ethz.ch/~fadouab/ ,\nhttps://www.yorku.ca/hkj/",
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      "title": "Estimate a Log-Concave Probability Mass Function from Discrete I.i.d. Observations",
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        "logcondiscr-package",
        "logcondiscr"
      ]
    },
    {
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      "title": "Functions for estimation of a log-concave probability mass function via maximum likelihood",
      "topics": [
        "Direction",
        "dMLE",
        "GradientL",
        "HesseL",
        "J00",
        "J10",
        "J11",
        "J20",
        "LikFunk",
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        "LocalConcavity",
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        "LocalNormalize",
        "StepSize"
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      "title": "Compute a mixture of a point mass at 0 and a log-concave probability mass function from i.i.d. data",
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        "kInflatedLogConDiscr"
      ]
    },
    {
      "page": "logConDiscrCI",
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      "topics": [
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      ]
    },
    {
      "page": "logConDiscrMLE",
      "title": "Compute log-concave probability mass function from i.i.d. data",
      "topics": [
        "logConDiscrMLE"
      ]
    },
    {
      "page": "Triangular",
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