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:
    non sort: A
    title: note on asymmetry and robustness in linear regression
  title info:
    title: American statistician
  name:
    name part: Carroll, Raymond J.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Welsh, A. H. (Alan H.)
    name part: 1960-
    role:
      role term: author.
  name:
    name part: Texas A & M University
    name part: Department of Statistics,
    role:
      role term: issuing body.
  name:
    name part: United States
    name part: Air Force.
    name part: Office of Scientific Research,
    role:
      role term: sponsoring 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: 7 leaves ; 28 cm
  abstract: We discuss the assumption of symmetry in robust linear regression. It is important to distinguish between the intercept term and the slope parameters. Ordinary robust regression requires no assumption of symmetry when interest lies in slope parameters; computer programs, confidence intervals, standard errors, etc. do not change because the errors are asymmetric. The situation is radically different for bounded influence estimators. With the exception of the Mallows class, these estimators are inconsistent for slope when the errors are asymmetric.
  note: Raymond J. Carroll and A.H. Welsh.
  note: Offprint: American statistician, Volume 42, pages 285-287.
  note: Funding information taken from leaf i.
  note: Includes bibliographical references (leaves 6-7).
  note: Supported by the Air Force Office of Scientific Research
  subject:
    topic: Regression analysis
  subject:
    topic: Robust statistics
  subject:
    topic: Error analysis (Mathematics)
  subject:
    topic: Symmetry (Mathematics)
  subject:
    topic: Estimation theory
    topic: Asymptotic theory
  subject:
    topic: Mathematical statistics
  subject:
    topic: Estimating equations
  subject:
    topic: Bounded influence estimation
  subject:
    topic: L-estimation
  subject:
    topic: M-estimation
  classification: QA276.A12 T4 no.13
  related item:
    title info:
      title: Technical report (Texas A & M University. Department of Statistics) ; no. 13
  record info:
    record content source: TXA
    record creation date: 180405
    record change date: 20180718085538.0
    record identifier: in00003931645
    language of cataloging:
      language term: eng