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: Statistical Estimation for Truncated Exponential Families
  name:
    name part: Akahira, Masafumi.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 122 p. 10 illus. online resource.
  abstract: This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping readers understand the meaning and implications of both regularity and irregularity through a certain family of distributions. In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This focus includes the (truncated) Pareto distribution, which is widely used in various fields such as finance, physics, hydrology, geology, astronomy, and other disciplines. The family is essential in that it links both regular and nonregular distributions, as it becomes a regular exponential family if the truncation parameter is known. The emphasis is on presenting new results on the maximum likelihood estimation of a natural parameter or truncation parameter if one of them is a nuisance parameter. In order to obtain more information on the truncation, the Bayesian approach is also considered. Further, the application to some useful truncated distributions is discussed. The illustrated clarification of the nonregular structure provides researchers and practitioners with a solid basis for further research and applications.
  note: by Masafumi Akahira.
  subject:
    topic: Statistics
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics and Computing/Statistics Programs
  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: SpringerBriefs in Statistics
  identifier: 9789811052965
  identifier: http://dx.doi.org/10.1007/978-981-10-5296-5
  record info:
    record creation date: 170727
    record change date: 20170727194110.0
    record identifier: 978-981-10-5296-5