Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "12542"
  #_source: array:26 [
    "id" => "12542"
    "slug" => "path-storage-in-the-particle-filter"
    "yearMonth" => "2015-03"
    "year" => "2015"
    "title" => "Path storage in the particle filter"
    "description" => "JACOB, P., MURRAY, L.M. et RUBENTHALER, S. (2015). Path storage in the particle filter. <i>Statistics and Computing</i>, 25(2), pp. 487-496."
    "authors" => array:3 [
      0 => array:3 [
        "name" => "JACOB Pierre"
        "bid" => "B00795650"
        "slug" => "jacob-pierre"
      ]
      1 => array:1 [
        "name" => "MURRAY Lawrence M."
      ]
      2 => array:1 [
        "name" => "RUBENTHALER Sylvain"
      ]
    ]
    "ouvrage" => ""
    "keywords" => []
    "updatedAt" => "2023-01-27 01:00:40"
    "publicationUrl" => "https://link.springer.com/article/10.1007/s11222-013-9445-x"
    "publicationInfo" => array:3 [
      "pages" => "487-496"
      "volume" => "25"
      "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" => "This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by T+CNlogN where T is the time horizon, N is the number of particles and C is a constant, as well as an efficient algorithm to realise this. The theoretical result and the algorithm are illustrated with numerical experiments."
      "en" => "This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by T+CNlogN where T is the time horizon, N is the number of particles and C is a constant, as well as an efficient algorithm to realise this. The theoretical result and the algorithm are illustrated with numerical experiments."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-22T11:21:42.000Z"
    "docTitle" => "Path storage in the particle filter"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/jacob-pierre">JACOB Pierre</a>, MURRAY Lawrence M., RUBENTHALER Sylvain"
    "docDescription" => "<span class="document-property-authors">JACOB Pierre, MURRAY Lawrence M., RUBENTHALER Sylvain</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2015</span>"
    "keywordList" => ""
    "docPreview" => "<b>Path storage in the particle filter</b><br><span>2015-03 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://link.springer.com/article/10.1007/s11222-013-9445-x" target="_blank">Path storage in the particle filter</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.594523
  +"parent": null
}