rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Analysis and Approximation of Rare Events
    sub title: Representations and Weak Convergence Methods
  name:
    name part: Budhiraja, Amarjit.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Dupuis, Paul.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 574 p. 14 illus., 1 illus. in color. online resource.
  abstract: This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities of interest such as normalized logarithms of probabilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers.
  table of contents: Preliminaries and elementary examples -- Discrete time processes -- Continuous time processes -- Monte Carlo approximation.
  note: by Amarjit Budhiraja, Paul Dupuis.
  subject:
    topic: Probabilities
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Numerical analysis
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Mathematical and Computational Engineering
  subject:
    topic: Numerical Analysis
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Probability Theory and Stochastic Modelling, 94
  identifier: 9781493995790
  identifier: https://doi.org/10.1007/978-1-4939-9579-0
  record info:
    record creation date: 190810
    record change date: 20191215161626.0
    record identifier: 978-1-4939-9579-0