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: Optimizing the smoothed bootstrap
  name:
    name part: Wang, Suojin
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Texas A & M University
    name part: Department of Statistics,
    role:
      role term: issuing body.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 1992
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: 12 leaves ; 28 cm
  abstract: The bootstrap and smoothed bootstrap have been shown to be a very powerful tool in statistics and its applications. In this paper, we develop the technique of rescaling in the smoothed bootstrap, extending Silverman and Young's (1987) idea of shrinking. Unlike most existing methods of smoothing, with a proper choice of the rescaling parameter the rescaled smoothed bootstrap method produces estimators that have the asymptotic minimum mean (integrated) squared error, and therefore outperforms the existing methods. The new method is investigated in the problems of estimation of global and local functionals and kernel density estimation.
  note: Suojin Wang.
  note: Funding information taken from leaf 11.
  note: Includes bibliographical references (leaf 12).
  note: Based in part upon work supported by the Texas Advanced Research Program under Grant No. 160802
  subject:
    geographic code: n-us-tx
  subject:
    topic: Bootstrap (Statistics)
  subject:
    topic: Smoothing (Statistics)
  subject:
    topic: Kernel functions
  subject:
    topic: Estimation theory
  subject:
    topic: Nonparametric statistics
  subject:
    topic: Mathematical statistics
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Density estimation
  subject:
    topic: Functional estimation
  subject:
    topic: Mean integrated squared error
  subject:
    topic: Mean squared error
  subject:
    topic: Rescaling
  subject:
    topic: Quantile
  classification: QA276.A12 T4 no.178
  related item:
    title info:
      title: Technical report (Texas A & M University. Department of Statistics) ; no. 178
  record info:
    record content source: TXA
    record creation date: 180403
    record change date: 20180403095346.0
    record identifier: in00003917660
    language of cataloging:
      language term: eng