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: Variance function estimation in regression
    sub title: the effect of estimating the mean
  title info:
    title: Journal of the Royal Statistical Society
    part number: Series B
    part name: Methodological
  name:
    name part: Hall, Peter
    name part: 1951-2016
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Carroll, Raymond J.
    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: 1987
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: 15 leaves ; 28 cm
  abstract: We consider estimation of a variance function g in regression problems. Such estimation requires simultaneous estimation of the mean function f. We obtain sharp results on the extent to which the smoothness of f influences best rates of convergence for estimating g. For example, in nonparametric regression with two derivatives on g, "classical" rates of convergence are possible if and only if the unknown f satisfies a Lipschitz condition of order 1/3 or more. If a parametric model is known for g, then g may be estimated n^1/2-consistently if and only if f is Lipschitz of order 1/2 or more. Optimal rates of convergence are attained by kernel estimators.
  note: Peter Hall and R.J. Carroll.
  note: The Cushing/Texas A&M Pubs. copy is missing leaf 14.
  note: Offprint: Journal of the Royal Statistical Society. Series B. Volume 51, pages 3-14.
  note: Includes bibliographical references (leaf 15).
  subject:
    topic: Regression analysis
  subject:
    topic: Nonparametric statistics
  subject:
    topic: Heteroscedasticity
  subject:
    topic: Convergence
  subject:
    topic: Kernel functions
  subject:
    topic: Smoothing (Statistics)
  subject:
    topic: Estimation theory
  subject:
    topic: Mathematical statistics
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Nonparametric regression
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Estimation
  subject:
    topic: Variance functions
  classification: QA276.A12 T4 no.4
  related item:
    title info:
      title: Technical report (Texas A & M University. Department of Statistics) ; no. 4
  record info:
    record content source: TXA
    record creation date: 180404
    record change date: 20200328063825.0
    record identifier: in00003963076
    language of cataloging:
      language term: eng