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: Fuzzy Statistics
  name:
    name part: Buckley, James J.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2004
    edition: 1st ed. 2004.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 168 p. online resource.
  abstract: This monograph introduces elementary fuzzy statistics based on crisp (non-fuzzy) data. In the introductory chapters the book presents a very readable survey of fuzzy sets including fuzzy arithmetic and fuzzy functions. The book develops fuzzy estimation and demonstrates the construction of fuzzy estimators for various important and special cases of variance, mean and distribution functions. It is shown how to use fuzzy estimators in hypothesis testing and regression, which leads to a comprehensive presentation of fuzzy hypothesis testing and fuzzy regression as well as fuzzy prediction.
  table of contents: Fuzzy Sets -- Estimate ?, Variance Known -- Estimate ?, Variance Unknown -- Estimate p, Binomial Population -- Estimate ?2 from a Normal Population -- Estimate µ 1 - µ 2, Variances Known -- Estimate ? 1 - ? 2, Variances Unknown -- Estimate d =? 1 - ? 2, Matched Pairs -- Estimate p 1 - p 2, Binomial Populations -- Estimate ? 1 2 /? 2 2 , Normal Populations -- Tests on µ, Variance Known -- Tests on µ, Variance Unknown -- Tests on p for a Binomial Population -- Tests on ? 2, Normal Population -- Tests ? 1 verses ? 2, Variances Known -- Test ? 1 verses ? 2, Variances Unknown -- Test p 1 = p 2, Binomial Populations -- Test d = µ 1 - µ 2 , Matched Pairs -- Test ? 1 2 verses ? 2 2 , Normal Populations -- Fuzzy Correlation -- Estimation in Simple Linear Regression -- Fuzzy Prediction in Linear Regression -- Hypothesis Testing in Regression -- Estimation in Multiple Regression -- Fuzzy Prediction in Regression -- Hypothesis Testing in Regression -- Summary and Questions -- Maple Commands.
  note: by James J. Buckley.
  subject:
    topic: Engineering
  subject:
    topic: Probabilities
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Statistics
  subject:
    topic: Computational complexity
  subject:
    topic: Engineering, general
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Mathematical and Computational Engineering
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Statistics, general
  subject:
    topic: Complexity
  classification: TA1-2040
  classification: 620
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 149
  identifier: 9783540399193
  identifier: https://doi.org/10.1007/978-3-540-39919-3
  record info:
    record creation date: 130909
    record change date: 20191022101751.0
    record identifier: 978-3-540-39919-3