Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "13717"
  #_source: array:26 [
    "id" => "13717"
    "slug" => "on-the-relation-between-extremal-dependence-and-concomitants"
    "yearMonth" => "2023-01"
    "year" => "2023"
    "title" => "On the relation between extremal dependence and concomitants"
    "description" => "KRATZ, M. et KHORAMI CHOKAMI, A. (2023). <i>On the relation between extremal dependence and concomitants</i>. WP 2301, ESSEC Business School Research Center."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "KRATZ Marie"
        "bid" => "B00072305"
        "slug" => "kratz-marie"
      ]
      1 => array:1 [
        "name" => "KHORAMI CHOKAMI Amir"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:14 [
      0 => "Asymptotic Theorems"
      1 => "Concomitants"
      2 => "Copula"
      3 => "(Tail) Dependence"
      4 => "Extremes"
      5 => "Gaussian"
      6 => "Logistic"
      7 => "Maxima"
      8 => "Order Statistics"
      9 => "Pareto"
      10 => "Slowly/Regularly"
      11 => "Varying Functions"
      12 => "Tail Equivalence"
      13 => "Weak Convergence"
    ]
    "updatedAt" => "2023-02-09 09:23:33"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => ""
      "volume" => ""
      "number" => ""
    ]
    "type" => array:2 [
      "fr" => "Documents de travail"
      "en" => "Working Papers"
    ]
    "support_type" => array:2 [
      "fr" => "Cahier de Recherche"
      "en" => "Working Papers"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "The study of concomitants has recently met a renewed interest due to its applications in selection procedures. For instance, concomitants are used in rankedset sampling, to achieve efficiency and reduce cost when compared to the simple random sampling. In parallel, the search for new methods to provide a rich description of extremal dependence among multiple time series has rapidly grown, due also to its numerous practical implications and the lack of suitable models to assess it. Here, our aim is to investigate extremal dependence when choosing the concomitants approach. In this study, we show how the extremal dependence of a vector (X, Y) impacts the asymptotic behavior of the maxima over subsets of concomitants. Furthermore, discussing the various conditions and results, we investigate how transformations of the marginal distributions of X and Y influence the degeneracy of the limit."
      "en" => "The study of concomitants has recently met a renewed interest due to its applications in selection procedures. For instance, concomitants are used in rankedset sampling, to achieve efficiency and reduce cost when compared to the simple random sampling. In parallel, the search for new methods to provide a rich description of extremal dependence among multiple time series has rapidly grown, due also to its numerous practical implications and the lack of suitable models to assess it. Here, our aim is to investigate extremal dependence when choosing the concomitants approach. In this study, we show how the extremal dependence of a vector (X, Y) impacts the asymptotic behavior of the maxima over subsets of concomitants. Furthermore, discussing the various conditions and results, we investigate how transformations of the marginal distributions of X and Y influence the degeneracy of the limit."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2024-04-20T03:21:45.000Z"
    "docTitle" => "On the relation between extremal dependence and concomitants"
    "docSurtitle" => "Documents de travail"
    "authorNames" => "<a href="/cv/kratz-marie">KRATZ Marie</a>, KHORAMI CHOKAMI Amir"
    "docDescription" => "<span class="document-property-authors">KRATZ Marie, KHORAMI CHOKAMI Amir</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2023</span>"
    "keywordList" => "<a href="#">Asymptotic Theorems</a>, <a href="#">Concomitants</a>, <a href="#">Copula</a>, <a href="#">(Tail) Dependence</a>, <a href="#">Extremes</a>, <a href="#">Gaussian</a>, <a href="#">Logistic</a>, <a href="#">Maxima</a>, <a href="#">Order Statistics</a>, <a href="#">Pareto</a>, <a href="#">Slowly/Regularly</a>, <a href="#">Varying Functions</a>, <a href="#">Tail Equivalence</a>, <a href="#">Weak Convergence</a>"
    "docPreview" => "<b>On the relation between extremal dependence and concomitants</b><br><span>2023-01 | Documents de travail </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">On the relation between extremal dependence and concomitants</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 8.637
  +"parent": null
}