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: Inference on the Hurst Parameter and the Variance of Diffusions Driven by Fractional Brownian Motion
  name:
    name part: Berzin, Corinne.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Latour, Alain.
    role:
      role term: author.
  name:
    name part: León, José R.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXVIII, 169 p. 26 illus., 17 illus. in color. online resource.
  abstract: This book is devoted to a number of stochastic models that display scale invariance. It primarily focuses on three issues: probabilistic properties, statistical estimation and simulation of the processes considered. It will be of interest to probability specialists, who will find here an uncomplicated presentation of statistics tools, and to those statisticians who wants to tackle the most recent theories in probability in order to develop Central Limit Theorems in this context; both groups will also benefit from the section on simulation. Algorithms are described in great detail, with a focus on procedures that is not usually found in mathematical treatises. The models studied are fractional Brownian motions and processes that derive from them through stochastic differential equations. Concerning the proofs of the limit theorems, the “Fourth Moment Theorem” is systematically used, as it produces rapid and helpful proofs that can serve as models for the future. Readers will also find elegant and new proofs for almost sure convergence. The use of diffusion models driven by fractional noise has been popular for more than two decades now. This popularity is due both to the mathematics itself and to its fields of application. With regard to the latter, fractional models are useful for modeling real-life events such as value assets in financial markets, chaos in quantum physics, river flows through time, irregular images, weather events, and contaminant diffus ion problems.
  table of contents: 1. Introduction -- 2. Preliminaries -- 3. Estimation of the Parameters -- 4. Simulation Algorithms and Simulation Studies -- 5. Proofs of all the results -- A. Complementary Results -- A.1. Introduction -- A.2. Proofs -- B. Tables and Figures Related to the Simulation Studies -- C. Some Pascal Procedures and Functions -- References -- Index.
  note: by Corinne Berzin, Alain Latour, José R. León.
  subject:
    topic: Statistics
  subject:
    topic: Computer simulation
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Simulation and Modeling
  subject:
    topic: Statistics for Business/Economics/Mathematical Finance/Insurance
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Statistics, 216
  identifier: 9783319078755
  identifier: http://dx.doi.org/10.1007/978-3-319-07875-5
  record info:
    record creation date: 141015
    record change date: 20151103130700.0
    record identifier: 978-3-319-07875-5