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: Multiparametric statistics
  name:
    name part: Serdobolskii, V.
    role:
      role term: creator
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  genre: dissertations.
  genre: Academic theses
  genre: Academic theses.
  genre: Thèses et écrits académiques.
  origin info:
    place:
      place term: ne
    place:
      place term: Amsterdam
    place:
      place term: Oxford
    publisher: Elsevier
    date issued: ©2008
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvii, 315 pages)
  abstract: This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters. This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution. Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. Near exact solutions are constructed for a number of concrete multi-dimensional problems: estimation of expectation vectors, regression and discriminant analysis, and for the solution to large systems of empiric linear algebraic equations. It is remarkable that these solutions prove to be not only non-degenerating and always stable, but also near exact within a wide class of populations. In the conventional situation of small dimension and large sample size these new solutions far surpass the classical, commonly used consistent ones. It can be expected in the near future, for the most part, traditional multivariate statistical software will be replaced by the always reliable and more efficient versions of statistical procedures implemented by the technology described in this book. This monograph will be of interest to a variety of specialists working with the theory of statistical methods and its applications. Mathematicians would find new classes of urgent pro…
  table of contents: Foreword -- Preface -- Chapter 1. Introduction: The Development of Multiparametric Statistics -- Chapter 2. Fundamental Problem of Statistics -- Chapter 3. Spectral Theory of Large Sample Covariance Matrices -- Chapter 4. Asymptitically Unimprovable Solution of Multivariate Problems -- Chapter 5. Multiparametric Discriminant Analysis -- Chapter 6. Theory of Solution to High-Order Systems of Empirical Linear Algebraic Equations -- Appendix -- References -- Index.
  note: Vadim I. Serdobolskii.
  note: Title from e-book title screen (viewed January 16, 2008).
  note: Includes bibliographical references and index.
  subject:
    topic: Multivariate analysis
  subject:
    topic: Analyse multivariée
  subject:
    topic: MATHEMATICS
    topic: Probability & Statistics
    topic: Multivariate Analysis
  subject:
    topic: Multivariate analysis
  classification: QA278 .S47 2008eb
  classification: 519.5/35
  related item:
    title info:
      title: Multiparametric statistics
    name:
      name part: Serdobolskii, V.
    origin info:
      publisher: Amsterdam ; Oxford : Elsevier, ©2008
    identifier: (DLC) 2009659305
  identifier: 0080555926
  identifier: 9780444530493
  identifier: 0444530495
  identifier: 9780080555928
  identifier: 2009659305
  identifier: 109629 MIL
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: UK-RwCLS
    record creation date: 070329
    record change date: 20260326153231.5
    record identifier: in00005734428
    language of cataloging:
      language term: eng