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: Boundary kernel estimation of the two sample comparison density function
  name:
    name part: Alexander, William Pyle
    name part: 1960-
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Texas A & M Research Foundation
  name:
    name part: Texas A & M University
    name part: Department of Statistics,
    role:
      role term: issuing body.
  name:
    name part: United States
    name part: Army Research Office,
    role:
      role term: sponsoring body.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 1989
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: v, 239 pages : illustrations ; 28 cm
  abstract: The focus of this work is to derive functional and graphical statistical techniques for the two sample problem suitable for implementation in modern computing environments. In the two sample problem, it is desired to test the null hypothesis that two independent random samples have a common distribution function. Assuming certain conditions on the distribution functions, a procedure is proposed which has strong graphical elements, a sound theoretical foundation, and estimates the relation of the two distributions if the null hypothesis is rejected. The proposed procedure has as its motivation the estimation of the comparison density and inference concerning its uniformity. The proposed procedure is both a statistical test of the null hypothesis and a model selection criterion. The test is based on components of a new stochastic process which is termed the kernel density process. This process is based on a boundary kernel estimate of the comparison density. It is proposed to apply a new test, the subset chi-square test, to these components. If the null hypothesis is rejected, the components found to be significant are used to construct a damped orthogonal series estimate of the comparison density. The power of the proposed test under local alternatives is compared to two commonly used portmanteau statistics, the Cramer-von Mises and the Anderson-Darling, and to a third statistic suggested by this work. A new method for finding the power of these statistics under local alternatives is given. This method uses the fast Fourier transform to invert an approximation to the characteristic function of the statistic. The proposed test is seen to have good power properties. A simulation study is conducted to examine its small sample size. Its size is found to remain close to its nominal value.
  note: by William Pyle Alexander.
  note: "May 1989."
  note: "Texas A & M Research Foundation, Project No. 5641."
  note: Includes bibliographical references (pages 183-190).
  note: Technical report.
  note: Sponsored by the U.S. Army Research Office DAAL03-87-K-0003
  subject:
    topic: Kernel functions
  subject:
    topic: Nonparametric statistics
  subject:
    topic: Estimation theory
  subject:
    topic: Sampling (Statistics)
  subject:
    topic: Smoothing (Statistics)
  subject:
    topic: Goodness-of-fit tests
  subject:
    topic: Empiricism
    topic: Statistical methods
  subject:
    topic: Mathematical statistics
  subject:
    topic: Statistics
    topic: Nonparametric inference
    topic: Density estimation
  subject:
    topic: Nonparametric statistics
  subject:
    topic: Smoothing (Statistics)
  subject:
    topic: Quantile data analysis
  subject:
    topic: Two sample non-parametric testing
  subject:
    topic: Comparison density function
  subject:
    topic: Components
  subject:
    topic: Boundary kernel density estimation
  related item:
    title info:
      title: Boundary kernel estimation of the two sample comparison density function
    name:
      name part: Alexander, William Pyle, 1960-
    origin info:
      publisher: 1989
    identifier: (OCoLC)20940631
  related item:
    title info:
      title: Technical report (Texas A & M University. Department of Statistics) ; no. 56
  record info:
    record content source: TXA
    record creation date: 990714
    record change date: 20191026063113.0
    record identifier: in00001496456
    language of cataloging:
      language term: eng