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: Heavy-Tail Phenomena
    sub title: Probabilistic and Statistical Modeling
  name:
    name part: Resnick, Sidney I.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 404 p. online resource.
  abstract: This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of phenomena where there is a significant probability of a single huge value impacting system behavior. Record-breaking insurance losses, financial returns, sizes of files stored on a server, transmission rates of files are all examples of heavy-tailed phenomena. Key features: Unique text devoted to heavy-tails. The treatment of heavy tails is largely dimensionless. The text gives attention to both probability modeling and statistical methods for fitting models. Most other books focus on one or the other but not both. The book emphasizes the broad applicability of heavy-tails to the fields of finance (e.g., value-at- risk), data networks, insurance. The presentation is clear, efficient and coherent and, balances theory and data analysis to show the applicability and limitations of certain methods. Several chapters examine in detail the mathematical properties of the methodologies as well as their implementation in the Splus or R statistical languages. The exposition is driven by numerous examples and exercises. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use (or at least to learn) a statistics package such as R or Splus. This work will serve second-year graduate students and researchers in the areas of operations research, statistics, applied mathematics, electrical engineering, financial engineering, networking and economics. Sidney Resnick is a Professor at Cornell University and has written several well-known bestsellers: A Probability Path (ISBN: 081764055X), Adventures in Stochastic Processes (ISBN: 0817635912) and Extreme Values, Regular Variation, and Point Processes (ISBN: 0387964819).
  table of contents: Crash Courses -- Crash Course I: Regular Variation -- Crash Course II: Weak Convergence; Implications for Heavy-Tail Analysis -- Statistics -- Dipping a Toe in the Statistical Water -- Probability -- The Poisson Process -- Multivariate Regular Variation and the Poisson Transform -- Weak Convergence and the Poisson Process -- Applied Probability Models and Heavy Tails -- More Statistics -- Additional Statistics Topics -- Appendices -- Notation and Conventions -- Software.
  note: by Sidney I. Resnick.
  subject:
    topic: Mathematics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Mathematical models
  subject:
    topic: Operations research
  subject:
    topic: Management science
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Applications of Mathematics
  subject:
    topic: Operations Research, Management Science
  subject:
    topic: Mathematical Modeling and Industrial Mathematics
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Series in Operations Research and Financial Engineering
  identifier: 9780387450247
  identifier: http://dx.doi.org/10.1007/978-0-387-45024-7
  record info:
    record creation date: 100301
    record change date: 20151204182459.0
    record identifier: 978-0-387-45024-7