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Computational Aspects of Model Choice

  • Conference proceedings
  • © 1993

Overview

Editors:
  1. Jaromír Antoch

    1. Department of Mathematical Statistics and Probability, Charles University, Prague 8, CSFR

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Part of the book series: Contributions to Statistics (CONTRIB.STAT.)

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Table of contents (11 papers)

  1. Front Matter

    Pages I-VII
    Download chapter PDF

  2. Tomáš Havránek

    • Jaromír Antoch
    Pages 1-5

  3. Bernd Streitberg

    • Jaromír Antoch
    Pages 7-10

  4. Change Point Problem

    • Jaromír Antoch, Marie Hušková
    Pages 11-37

  5. Robust Estimation in Linear Model and its Computational Aspects

    • Jaromír Antoch, Jan Ámos Víšek
    Pages 39-104

  6. Constructing Prediction Trees from Data: The RECPAM Approach

    • Antonio Ciampi
    Pages 105-152

  7. Stochastic Approximation and Optimization

    • Václav Dupač
    Pages 153-161

  8. Comparison of the Stochastic Approximation Software

    • Pavel Charamza
    Pages 163-176

  9. Models, Algorithms and Software of Stochastic Optimization

    • Victor Loskutov
    Pages 177-186

  10. Some Computational Aspects of Graphical Model Selection

    • David Edwards
    Pages 187-210

  11. Multiple Hypotheses Testing

    • Gerhard Hommel, Gudrun Bernhard
    Pages 211-235

  12. Statistical Applications of Artificial Intelligence

    • William A. Gale
    Pages 237-285
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Keywords

About this book

Although no-one is, probably, too enthused about the idea, it is a fact that the development of most empirical sciences to a great extend depends of the development of data analysis methods and techniques, which, due to the necessity of applications of computers for that pur­ pose, actually means that it practically depends on the advancements and orientation of computational statistics. This volume contains complete texts of the lectures held during the Summer School on "Computational Aspects of Model Choice" orga­ nized jointly by Charles University, Prague, and International Associa­ tion for Statistical Computing (IASC) on July 1-14, 1991, in Prague. Main aims of the Summer School were to review and analyse some of the recent developments concerning computational aspects of the model choice as well as their theoretical background. The topics covers the problems of the change point detection, robust estimation and its computational aspects, classification using binary trees, stochastic ap­ proximation and optimization including the discussion about available software, computational aspects of graphical model selection and mul­ tiple hypotheses testing. The bridge between these different approaches is formed by the survey paper about statistical applications of artificial intelligence.

Editors and Affiliations

  • Department of Mathematical Statistics and Probability, Charles University, Prague 8, CSFR

    Jaromír Antoch

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