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: Random Number Generation and Monte Carlo Methods
  name:
    name part: Gentle, James E.
    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: 2003
    edition: Second Edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 382 p. online resource.
  abstract: Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These "pseudorandom" numbers must pass statistical tests just as random samples would. Methods for producing pseudorandom numbers and transforming those numbers to simulate samples from various distributions are among the most important topics in statistical computing. This book surveys techniques of random number generation and the use of random numbers in Monte Carlo simulation. The book covers basic principles, as well as newer methods such as parallel random number generation, nonlinear congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo. The best methods for generating random variates from the standard distributions are presented, but also general techniques useful in more complicated models and in novel settings are described. The emphasis throughout the book is on practical methods that work well in current computing environments. The book includes exercises and can be used as a test or supplementary text for various courses in modern statistics. It could serve as the primary test for a specialized course in statistical computing, or as a supplementary text for a course in computational statistics and other areas of modern statistics that rely on simulation. The book, which covers recent developments in the field, could also serve as a useful reference for practitioners. Although some familiarity with probability and statistics is assumed, the book is accessible to a broad audience. The second edition is approximately 50% longer than the first edition. It includes advances in methods for parallel random number generation, universal methods for generation of nonuniform variates, perfect sampling, and software for random number generation.
  table of contents: Simulating Random Numbers from a Uniform Distribution -- Quality of Random Number Generators -- Quasirandom Numbers -- Transformations of Uniform Deviates: General Methods -- Simulating Random Numbers from Specific Distributions -- Generation of Random Samples, Permutations, and Stochastic Processes -- Monte Carlo Methods -- Software for Random Number Generation -- Monte Carlo Studies in Statistics.
  note: by James E. Gentle.
  subject:
    topic: Statistics
  subject:
    topic: Numerical analysis
  subject:
    topic: Statistics
  subject:
    topic: Statistics and Computing/Statistics Programs
  subject:
    topic: Numerical Analysis
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Statistics and Computing
  identifier: 9780387216102
  identifier: http://dx.doi.org/10.1007/b97336
  record info:
    record creation date: 100301
    record change date: 20151204181331.0
    record identifier: 978-0-387-21610-2