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: Using the bootstrap to analyze variable stars data
  name:
    name part: Dunlap, Mickey Paul, 1972-
    role:
      role term: creator
  name:
    name part: Hart, Jeffrey D.
    role:
      role term: thesis advisor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2005
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: remote
  abstract: Often in statistics it is of interest to investigate whether or not a trend is signficant. Methods for testing such a trend depend on the assumptions of the error terms such as whether the distribution is known and also if the error terms are independent. Likelihood ratio tests may be used if the distribution is known but in some instances one may not want to make such assumptions. In a time series, these errors will not always be independent. In this case, the error terms are often modelled by an autoregressive or moving average process. There are resampling techniques for testing the hypothesis of interest when the error terms are dependent, such as, model-based bootstrapping and the wild bootstrap, but the error terms need to be whitened. In this dissertation, a bootstrap procedure is used to test the hypothesis of no trend for variable stars when the error structure assumes a particular form. In some cases, the bootstrap to be implemented is preferred over large sample tests in terms of the level of the test. The bootstrap procedure is able to correctly identify the underlying distribution which may not be [Chi]².
  note: by Mickey Paul Dunlap.
  note: "Major Subject: Statistics"
  note: Title from author supplied metadata (automated record created on Feb. 17, 2005.)
  note: Vita.
  note: Abstract.
  note: Electronic resource.
  note: Mode of access: World Wide Web.
  note: System requirements: World Wide Web access and Adobe Acrobat Reader.
  note: Ph. D. Texas A&M University 2004.
  note: Includes bibliographical references.
  note: Text (Dissertation).
  subject:
    topic: Major statistics
  subject:
    topic: Variable Stars
  subject:
    topic: Dependent Data
  subject:
    topic: Bootstrap
  identifier: http://hdl.handle.net/1969.1/1398
  record info:
    record content source: TXA
    record creation date: 050523
    record change date: 20151101174451.0
    record identifier: in00002050206