Universidad de Burgos RIUBU Principal Default Universidad de Burgos RIUBU Principal Default
  • español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
Universidad de Burgos RIUBU Principal Default
  • Ayuda
  • Contact Us
  • Send Feedback
  • Acceso abierto
    • Archivar en RIUBU
    • Acuerdos editoriales para la publicación en acceso abierto
    • Controla tus derechos, facilita el acceso abierto
    • Sobre el acceso abierto y la UBU
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of RIUBUCommunities and CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Compartir

    View Item 
    •   RIUBU Home
    • E-Prints
    • Untitled
    • Untitled
    • Untitled
    • View Item
    •   RIUBU Home
    • E-Prints
    • Untitled
    • Untitled
    • Untitled
    • View Item

    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/3842

    Título
    Stochastic Approximation to Understand Simple Simulation Models
    Autor
    Izquierdo, Segismundo S.
    Izquierdo Millán, Luis RodrigoUBU authority Orcid
    Publicado en
    Journal of Statistical Physics. 2013, V. 151, n. 1, p. 254-276
    Editorial
    Springer Verlag (Germany)
    Fecha de publicación
    2013-04
    ISSN
    0022-4715
    DOI
    10.1007/s10955-012-0654-z
    Abstract
    This paper illustrates how a deterministic approximation of a stochastic process can be usefully applied to analyse the dynamics of many simple simulation models. To demonstrate the type of results that can be obtained using this approximation, we present two illustrative examples which are meant to serve as methodological references for researchers exploring this area. Finally, we prove some convergence results for simulations of a family of evolutionary games, namely, intra-population imitation models in n-player games with arbitrary payoffs.
    Palabras clave
    Stochastic approximation
    Mean dynamic
    Markov models
    Evolutionary games
    Materia
    Gestión de empresas
    Industrial management
    URI
    http://hdl.handle.net/10259/3842
    Versión del editor
    http://dx.doi.org/10.1007/s10955-012-0654-z
    Collections
    • Untitled
    Files in this item
    Nombre:
    Izquierdo-JSP_2013.pdf
    Tamaño:
    896.3Kb
    Formato:
    Adobe PDF
    Thumbnail
    FilesOpen

    Métricas

    Citas

    Academic Search
    Ver estadísticas de uso

    Export

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis
    Show full item record