Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "2194"
  #_source: array:26 [
    "id" => "2194"
    "slug" => "partial-least-squares-algorithms-and-methods"
    "yearMonth" => "2014-11"
    "year" => "2014"
    "title" => "Partial Least Squares Algorithms and Methods"
    "description" => "ESPOSITO VINZI, V. et RUSOLILLO, G. (2014). Partial Least Squares Algorithms and Methods. <i>Wires Computational Statistics</i>, 5, pp. 1-19."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "ESPOSITO VINZI Vincenzo"
        "bid" => "B00067049"
        "slug" => "esposito-vinzi-vincenzo"
      ]
      1 => array:1 [
        "name" => "RUSOLILLO G."
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:3 [
      0 => "Modèles à équations structurelles"
      1 => "Régression"
      2 => "Tableaux multiples"
    ]
    "updatedAt" => "2021-02-02 16:16:18"
    "publicationUrl" => "https://doi.org/10.1002/wics.1239"
    "publicationInfo" => array:3 [
      "pages" => "1-19"
      "volume" => "5"
      "number" => null
    ]
    "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" => "Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that implement a broad spectrum of both explanatory and exploratory multivariate techniques, from regression to path modeling, and from principal component to multi-block data analysis. This article focuses on PLS regression and PLS path modeling, which are PLS approaches to regularized regression and to predictive path modeling. The computational flows and the optimization criteria of these methods are reviewed in detail, as well as the tools for the assessment and interpretation of PLS models. The most recent developments and some of the most promising on going researches are enhanced."
      "en" => "Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that implement a broad spectrum of both explanatory and exploratory multivariate techniques, from regression to path modeling, and from principal component to multi-block data analysis. This article focuses on PLS regression and PLS path modeling, which are PLS approaches to regularized regression and to predictive path modeling. The computational flows and the optimization criteria of these methods are reviewed in detail, as well as the tools for the assessment and interpretation of PLS models. The most recent developments and some of the most promising on going researches are enhanced."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2024-04-19T17:22:15.000Z"
    "docTitle" => "Partial Least Squares Algorithms and Methods"
    "docSurtitle" => "Articles"
    "authorNames" => "<a href="/cv/esposito-vinzi-vincenzo">ESPOSITO VINZI Vincenzo</a>, RUSOLILLO G."
    "docDescription" => "<span class="document-property-authors">ESPOSITO VINZI Vincenzo, RUSOLILLO G.</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2014</span>"
    "keywordList" => "<a href="#">Modèles à équations structurelles</a>, <a href="#">Régression</a>, <a href="#">Tableaux multiples</a>"
    "docPreview" => "<b>Partial Least Squares Algorithms and Methods</b><br><span>2014-11 | Articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1002/wics.1239" target="_blank">Partial Least Squares Algorithms and Methods</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 8.961621
  +"parent": null
}