Analysis and approximation of rare events : representations and weak convergence methods

著者

書誌事項

Analysis and approximation of rare events : representations and weak convergence methods

Amarjit Budhiraja, Paul Dupuis

(Probability theory and stochastic modelling, v. 94)

Springer, c2019

  • : pbk

大学図書館所蔵 件 / 1

この図書・雑誌をさがす

注記

Includes bibliographical references (p. 559-569) and index

内容説明・目次

内容説明

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.

目次

Preliminaries and elementary examples.- Discrete time processes.- Continuous time processes.- Monte Carlo approximation.

「Nielsen BookData」 より

関連文献: 1件中  1-1を表示

詳細情報

  • NII書誌ID(NCID)
    BC04883718
  • ISBN
    • 9781493996223
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    [New York]
  • ページ数/冊数
    xix, 574 p.
  • 大きさ
    24 cm
  • 親書誌ID
ページトップへ