Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "9788"
  #_source: array:26 [
    "id" => "9788"
    "slug" => "the-q-q-estimator-and-heavy-tails"
    "yearMonth" => "1996-04"
    "year" => "1996"
    "title" => "The Q-Q estimator and heavy tails"
    "description" => "KRATZ, M. et RESNICK, S. (1996). The Q-Q estimator and heavy tails. <i>Stochastic Models</i>, 12(4), pp. 699-724."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "KRATZ Marie"
        "bid" => "B00072305"
        "slug" => "kratz-marie"
      ]
      1 => array:1 [
        "name" => "RESNICK Sidney"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:3 [
      0 => "AMS classification -parameter estimation"
      1 => "weak convergence"
      2 => "consistency -time series analysis -qq-plot -heavy tails -regular variation"
    ]
    "updatedAt" => "2021-07-13 14:31:20"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => "699-724"
      "volume" => "12"
      "number" => "4"
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "A common visual technique for assessing goodness of fit and estimating location and scale is the qq--plot. We apply this technique to data from a Pareto distribution and more generally to data generated by a distribution with a heavy tail. A procedure for assessing the presence of heavy tails and for estimating the parameter of regular variation is discussed which can supplement other standard techniques such as the Hill plot. Some examples are given using telecommunications data."
      "en" => "A common visual technique for assessing goodness of fit and estimating location and scale is the qq--plot. We apply this technique to data from a Pareto distribution and more generally to data generated by a distribution with a heavy tail. A procedure for assessing the presence of heavy tails and for estimating the parameter of regular variation is discussed which can supplement other standard techniques such as the Hill plot. Some examples are given using telecommunications data."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-03T17:21:44.000Z"
    "docTitle" => "The Q-Q estimator and heavy tails"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/kratz-marie">KRATZ Marie</a>, RESNICK Sidney"
    "docDescription" => "<span class="document-property-authors">KRATZ Marie, RESNICK Sidney</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">1996</span>"
    "keywordList" => "<a href="#">AMS classification -parameter estimation</a>, <a href="#">weak convergence</a>, <a href="#">consistency -time series analysis -qq-plot -heavy tails -regular variation</a>"
    "docPreview" => "<b>The Q-Q estimator and heavy tails</b><br><span>1996-04 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">The Q-Q estimator and heavy tails</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.697312
  +"parent": null
}