Markov processes, Gaussian processes...
Marcus, Michael B.,

 

  • Markov processes, Gaussian processes, and local times /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 519.2/33
    書名/作者: Markov processes, Gaussian processes, and local times // Michael B. Marcus, Jay Rosen.
    其他題名: Markov Processes, Gaussian Processes, & Local Times
    作者: Marcus, Michael B.,
    其他作者: Rosen, Jay,
    面頁冊數: 1 online resource (x, 620 pages) : : digital, PDF file(s).
    附註: Title from publisher's bibliographic system (viewed on 05 Oct 2015).
    標題: Markov processes.
    標題: Gaussian processes.
    標題: Local times (Stochastic processes)
    ISBN: 9780511617997 (ebook)
    內容註: Brownian motion and Ray-Knight theorems -- Markov processes and local times -- Constructing Markov processes -- Basic properties of Gaussian processes -- Continuity and boundedness of Gaussian processes -- Moduli of continuity for Gaussian processes -- Isomorphism theorems -- Sample path properties of local times -- [Rho]-variation -- Most visited sites of symmetric stable processes -- Local times of diffusions -- Associated Gaussian processes.
    摘要、提要註: This book was first published in 2006. Written by two of the foremost researchers in the field, this book studies the local times of Markov processes by employing isomorphism theorems that relate them to certain associated Gaussian processes. It builds to this material through self-contained but harmonized 'mini-courses' on the relevant ingredients, which assume only knowledge of measure-theoretic probability. The streamlined selection of topics creates an easy entrance for students and experts in related fields. The book starts by developing the fundamentals of Markov process theory and then of Gaussian process theory, including sample path properties. It then proceeds to more advanced results, bringing the reader to the heart of contemporary research. It presents the remarkable isomorphism theorems of Dynkin and Eisenbaum and then shows how they can be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original, readable book will appeal to both researchers and advanced graduate students.
    電子資源: http://dx.doi.org/10.1017/CBO9780511617997
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