Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "6718"
  #_source: array:26 [
    "id" => "6718"
    "slug" => "multi-component-estimation-of-pls-predictive-path-modeling"
    "yearMonth" => "2011-08"
    "year" => "2011"
    "title" => "Multi-component Estimation of PLS Predictive Path Modeling"
    "description" => "TRINCHERA, L., RUSSOLILLO, G. et ESPOSITO VINZI, V. (2011). Multi-component Estimation of PLS Predictive Path Modeling. Dans: 58th World Statistics Congress of the International Statistical Institute (ISI 2011)."
    "authors" => array:3 [
      0 => array:3 [
        "name" => "ESPOSITO VINZI Vincenzo"
        "bid" => "B00067049"
        "slug" => "esposito-vinzi-vincenzo"
      ]
      1 => array:1 [
        "name" => "TRINCHERA L."
      ]
      2 => array:1 [
        "name" => "RUSSOLILLO G."
      ]
    ]
    "ouvrage" => "58th World Statistics Congress of the International Statistical Institute (ISI 2011)"
    "keywords" => []
    "updatedAt" => "2021-04-19 17:57:25"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => null
      "volume" => null
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Communications dans une conférence"
      "en" => "Presentations at an Academic or Professional conference"
    ]
    "support_type" => array:2 [
      "fr" => null
      "en" => null
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => """
        We present a new approach to estimating outer weights in PLS Path Modeling that is fully based on the PLS principle. Two new modes are presented for estimating the measurement model: PLScore Mode with standardized scores and oriented to maximizing correlations between\n
        latent variables (LVs); PLScow Mode with constrained weights and oriented to maximizing covariances between LVs. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression.
        """
      "en" => """
        We present a new approach to estimating outer weights in PLS Path Modeling that is fully based on the PLS principle. Two new modes are presented for estimating the measurement model: PLScore Mode with standardized scores and oriented to maximizing correlations between\n
        latent variables (LVs); PLScow Mode with constrained weights and oriented to maximizing covariances between LVs. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression.
        """
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2024-04-16T15:22:01.000Z"
    "docTitle" => "Multi-component Estimation of PLS Predictive Path Modeling"
    "docSurtitle" => "Communications dans une conférence"
    "authorNames" => "<a href="/cv/esposito-vinzi-vincenzo">ESPOSITO VINZI Vincenzo</a>, TRINCHERA L., RUSSOLILLO G."
    "docDescription" => "<span class="document-property-authors">ESPOSITO VINZI Vincenzo, TRINCHERA L., RUSSOLILLO G.</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2011</span>"
    "keywordList" => ""
    "docPreview" => "<b>Multi-component Estimation of PLS Predictive Path Modeling</b><br><span>2011-08 | Communications dans une conférence </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">Multi-component Estimation of PLS Predictive Path Modeling</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 9.23802
  +"parent": null
}