<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-01256008</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-20T10:44:09+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Dimension reduction in multivariate extreme value analysis</title>
            <author role="aut">
              <persName>
                <forename type="first">Emilie</forename>
                <surname>Chautru</surname>
              </persName>
              <email type="md5">d7e418182bd0a0ff941c2d922f6edfeb</email>
              <email type="domain">telecom-paristech.org</email>
              <idno type="idhal" notation="string">emilie-chautru</idno>
              <idno type="idhal" notation="numeric">12509</idno>
              <idno type="halauthorid" notation="string">29841-12509</idno>
              <idno type="IDREF">https://www.idref.fr/192802925</idno>
              <idno type="ORCID">https://orcid.org/0009-0002-1613-2246</idno>
              <affiliation ref="#struct-43221"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Bibliothèque</forename>
                <surname>MINES ParisTech</surname>
              </persName>
              <email type="md5">d5de782aedb4272557b1be8346514619</email>
              <email type="domain">mines-paristech.fr</email>
            </editor>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2016-01-14 11:32:05</date>
              <date type="whenWritten">2013-12</date>
              <date type="whenModified">2026-01-09 09:46:02</date>
              <date type="whenReleased">2016-01-14 15:14:37</date>
              <date type="whenProduced">2015</date>
              <date type="whenEndEmbargoed">2016-01-14</date>
              <ref type="file" target="https://minesparis-psl.hal.science/hal-01256008v1/document">
                <date notBefore="2016-01-14"/>
              </ref>
              <ref type="file" subtype="greenPublisher" n="1" target="https://minesparis-psl.hal.science/hal-01256008v1/file/euclid.ejs.1426611768.pdf" id="file-1256008-1335592">
                <date notBefore="2016-01-14"/>
              </ref>
              <ref type="externalLink" target="https://doi.org/10.1214/15-ejs1002"/>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="145907">
                <persName>
                  <forename>Bibliothèque</forename>
                  <surname>MINES ParisTech</surname>
                </persName>
                <email type="md5">d5de782aedb4272557b1be8346514619</email>
                <email type="domain">mines-paristech.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-01256008</idno>
            <idno type="halUri">https://minesparis-psl.hal.science/hal-01256008</idno>
            <idno type="halBibtex">chautru:hal-01256008</idno>
            <idno type="halRefHtml">&lt;i&gt;Electronic Journal of Statistics &lt;/i&gt;, 2015, 9 (1), pp.383-418. &lt;a target="_blank" href="https://dx.doi.org/10.1214/15-EJS1002"&gt;&amp;#x27E8;10.1214/15-EJS1002&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">Electronic Journal of Statistics , 2015, 9 (1), pp.383-418. &amp;#x27E8;10.1214/15-EJS1002&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0 - Attribution<ref corresp="#file-1256008-1335592"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="ENSMP" corresp="PARISTECH">MINES ParisTech</idno>
            <idno type="stamp" n="ENSMP_GEOSCIENCES" corresp="ENSMP">Géosciences (GEOSCIENCES)</idno>
            <idno type="stamp" n="PARISTECH">ParisTech</idno>
            <idno type="stamp" n="PSL">Université Paris sciences et lettres</idno>
            <idno type="stamp" n="ENSMP_DEP_STE" corresp="ENSMP">Département Sciences de la Terre et de l’Environnement</idno>
            <idno type="stamp" n="ENSMP_GEOSTAT" corresp="ENSMP_GEOSCIENCES">équipe de Géostatistique</idno>
            <idno type="stamp" n="ENSMP_DR" corresp="ENSMP">ENSMP_DR</idno>
            <idno type="stamp" n="ENSMP-PSL" corresp="PSL">MINES ParisTech - École nationale supérieure des mines de Paris - PSL</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Dimension reduction in multivariate extreme value analysis</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Emilie</forename>
                    <surname>Chautru</surname>
                  </persName>
                  <email type="md5">d7e418182bd0a0ff941c2d922f6edfeb</email>
                  <email type="domain">telecom-paristech.org</email>
                  <idno type="idhal" notation="string">emilie-chautru</idno>
                  <idno type="idhal" notation="numeric">12509</idno>
                  <idno type="halauthorid" notation="string">29841-12509</idno>
                  <idno type="IDREF">https://www.idref.fr/192802925</idno>
                  <idno type="ORCID">https://orcid.org/0009-0002-1613-2246</idno>
                  <affiliation ref="#struct-43221"/>
                </author>
              </analytic>
              <monogr>
                <idno type="halJournalId" status="VALID">104512</idno>
                <idno type="issn">1935-7524</idno>
                <idno type="eissn">1935-7524</idno>
                <title level="j">Electronic Journal of Statistics </title>
                <imprint>
                  <publisher>Shaker Heights, OH : Institute of Mathematical Statistics</publisher>
                  <biblScope unit="volume">9</biblScope>
                  <biblScope unit="issue">1</biblScope>
                  <biblScope unit="pp">383-418</biblScope>
                  <date type="datePub">2015</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1214/15-EJS1002</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en"> multivariate extremes</term>
                <term xml:lang="en"> extreme dependence</term>
                <term xml:lang="en"> mixture model</term>
                <term xml:lang="en"> latent variable</term>
                <term xml:lang="en"> dimension reduction</term>
                <term xml:lang="en">Angular/spectral measure</term>
              </keywords>
              <classCode scheme="halDomain" n="stat">Statistics [stat]</classCode>
              <classCode scheme="halTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halOldTypology" n="ART">Journal articles</classCode>
              <classCode scheme="halTreeTypology" n="ART">Journal articles</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>Non-parametric assessment of extreme dependence structures between an arbitrary number of variables, though quite well-established in dimension 2 and recently extended to moderate dimensions such as 5, still represents a statistical challenge in larger dimensions. Here, we propose a novel approach that combines clustering techniques with angular/spectral measure analysis to find groups of variables (not necessarily disjoint) exhibiting asymptotic dependence, thereby reducing the dimension of the initial problem. A heuristic criterion is proposed to choose the threshold over which it is acceptable to consider observations as extreme and the appropriate number of clusters. When empirically evaluated through numerical experiments, the approach we promote here is found to be very efficient under some regularity constraints, even in dimension 20. For illustration purpose, we also carry out a case study in dietary risk assessment.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="laboratory" xml:id="struct-43221" status="VALID">
          <idno type="IdRef">151289468</idno>
          <idno type="RNSR">200920615Y</idno>
          <idno type="ROR">https://ror.org/03kc13263</idno>
          <orgName>Centre de Géosciences</orgName>
          <orgName type="acronym">GEOSCIENCES</orgName>
          <desc>
            <address>
              <addrLine>35 rue Saint-Honoré 77305 Fontainebleau cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.geosciences.mines-paristech.fr</ref>
          </desc>
          <listRelation>
            <relation active="#struct-301492" type="direct"/>
            <relation active="#struct-564132" type="indirect"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-301492" status="VALID">
          <idno type="IdRef">026375249</idno>
          <idno type="ROR">https://ror.org/04y8cs423</idno>
          <orgName>Mines Paris - PSL (École nationale supérieure des mines de Paris)</orgName>
          <date type="start">1783-01-01</date>
          <desc>
            <address>
              <addrLine>60, boulevard Saint-Michel 75006 Paris</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.minesparis.psl.eu/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-564132" type="direct"/>
          </listRelation>
        </org>
        <org type="regroupinstitution" xml:id="struct-564132" status="VALID">
          <idno type="IdRef">241597595</idno>
          <idno type="ISNI">0000 0004 1784 3645</idno>
          <idno type="ROR">https://ror.org/013cjyk83</idno>
          <orgName>Université Paris Sciences et Lettres</orgName>
          <orgName type="acronym">PSL</orgName>
          <desc>
            <address>
              <addrLine>60 rue Mazarine 75006 Paris</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.psl.eu/</ref>
          </desc>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>