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Essec\Faculty\Model\Contribution {#2216 ▼
  #_index: "academ_contributions"
  #_id: "12752"
  #_source: array:26 [
    "id" => "12752"
    "slug" => "12752-robust-and-efficient-mean-estimation-an-approach-based-on-the-properties-of-self-normalized-sums 12752-robust-and-efficient-mean-estimation-an-approach-based-on-the-properties-of-self-normalized-su "
    "yearMonth" => "2021-12"
    "year" => "2021"
    "title" => "Robust and efficient mean estimation: an approach based on the properties of self-normalized sums"
    "description" => "MINSKER, S. et NDAOUD, M. (2021). Robust and efficient mean estimation: an approach based on the properties of self-normalized sums. <i>The Electronic Journal of Statistics</i>, 15(2), pp. 6036-6070. MINSKER, S. et NDAOUD, M. (2021). Robust and efficient mean estimation: an approach based on the pro "
    "authors" => array:2 [
      0 => array:3 [
        "name" => "NDAOUD Mohamed"
        "bid" => "B00791786"
        "slug" => "ndaoud-mohamed"
      ]
      1 => array:1 [
        "name" => "MINSKER Stanislav"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:4 [
      0 => "efficiency"
      1 => "robust estimation"
      2 => "self-normalized sums"
      3 => "sub-Gaussian deviations"
    ]
    "updatedAt" => "2023-07-10 16:47:23"
    "publicationUrl" => "https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-15/issue-2/Robust-and-efficient-mean-estimation--an-approach-based-on/10.1214/21-EJS1925.full https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-15/issue-2/Robust-and-eff "
    "publicationInfo" => array:3 [
      "pages" => "6036-6070"
      "volume" => "15"
      "number" => "2"
    ]
    "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" => "Let X be a random variable with unknown mean and finite variance. We present a new estimator of the mean of X that is robust with respect to the possible presence of outliers in the sample, provides tight sub-Gaussian deviation guarantees without any additional assumptions on the shape or tails of the distribution, and moreover is asymptotically efficient. This is the first estimator that provably combines all these qualities in one package. Our construction is inspired by robustness properties possessed by the self-normalized sums. Theoretical findings are supplemented by numerical simulations highlighting strong performance of the proposed estimator in comparison with previously known techniques. Let X be a random variable with unknown mean and finite variance. We present a new estimator of the  "
      "en" => "Let X be a random variable with unknown mean and finite variance. We present a new estimator of the mean of X that is robust with respect to the possible presence of outliers in the sample, provides tight sub-Gaussian deviation guarantees without any additional assumptions on the shape or tails of the distribution, and moreover is asymptotically efficient. This is the first estimator that provably combines all these qualities in one package. Our construction is inspired by robustness properties possessed by the self-normalized sums. Theoretical findings are supplemented by numerical simulations highlighting strong performance of the proposed estimator in comparison with previously known techniques. Let X be a random variable with unknown mean and finite variance. We present a new estimator of the  "
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2025-04-09T00:21:42.000Z"
    "docTitle" => "Robust and efficient mean estimation: an approach based on the properties of self-normalized sums"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/ndaoud-mohamed">NDAOUD Mohamed</a>, MINSKER Stanislav"
    "docDescription" => "<span class="document-property-authors">NDAOUD Mohamed, MINSKER Stanislav</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2021</span> <span class="document-property-authors">NDAOUD Mohamed, MINSKER Stanislav</span><br><span class="doc "
    "keywordList" => "<a href="#">efficiency</a>, <a href="#">robust estimation</a>, <a href="#">self-normalized sums</a>, <a href="#">sub-Gaussian deviations</a> <a href="#">efficiency</a>, <a href="#">robust estimation</a>, <a href="#">self-normalized sums</a>, "
    "docPreview" => "<b>Robust and efficient mean estimation: an approach based on the properties of self-normalized sums</b><br><span>2021-12 | Journal articles </span> <b>Robust and efficient mean estimation: an approach based on the properties of self-normalized sums "
    "docType" => "research"
    "publicationLink" => "<a href="https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-15/issue-2/Robust-and-efficient-mean-estimation--an-approach-based-on/10.1214/21-EJS1925.full" target="_blank">Robust and efficient mean estimation: an approach based on the properties of self-normalized sums</a> <a href="https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-15/issue-2/Robus "
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 9.057423
  +"parent": null
}