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: Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem
    sub title: with Simulations and Examples in SAS®
  name:
    name part: Desai, Tejas.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: V, 55 p. online resource.
  abstract: In statistics, the Behrens–Fisher problem is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples. In his 1935 paper, Fisher outlined an approach to the Behrens-Fisher problem. Since high-speed computers were not available in Fisher’s time, this approach was not implementable and was soon forgotten. Fortunately, now that high-speed computers are available, this approach can easily be implemented using just a desktop or a laptop computer. Furthermore, Fisher’s approach was proposed for univariate samples. But this approach can also be generalized to the multivariate case. In this monograph, we present the solution to the afore-mentioned multivariate generalization of the Behrens-Fisher problem. We start out by presenting a test of multivariate normality, proceed to test(s) of equality of covariance matrices, and end with our solution to the multivariate Behrens-Fisher problem. All methods proposed in this monograph will be include both the randomly-incomplete-data case as well as the complete-data case. Moreover, all methods considered in this monograph will be tested using both simulations and examples.
  table of contents: Introduction -- On Testing for Multivariate Normality -- On Testing Equality of Covariance Matrices -- On Heteroscedastic MANOVA -- References.
  note: by Tejas Desai.
  subject:
    topic: Statistics
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics, general
  subject:
    topic: Statistics and Computing/Statistics Programs
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Statistics
  identifier: 9781461464433
  identifier: http://dx.doi.org/10.1007/978-1-4614-6443-3
  record info:
    record creation date: 130228
    record change date: 20151204153252.0
    record identifier: 978-1-4614-6443-3