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Computational Statistics

Volume 1: Proceedings of the 10th Symposium on Computational Statistics

  • Conference proceedings
  • © 1992

Overview

Editors:
  1. Yadolah Dodge

    1. Groupe de Statistique, University of Neuchâtel, Neuchâtel, Switzerland

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  2. Joe Whittaker

    1. Lancaster University, GB-Lancaster, Great Britain

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    You can also search for this editor in PubMed   Google Scholar

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Table of contents (78 papers)

  1. Front Matter

    Pages I-XVI
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  2. Prologue

    1. Front Matter

      Pages 1-1
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    2. Science, Data, Statistics and Computing

      • Yadolah Dodge, Joe Whittaker
      Pages 3-7

  3. Statistical Modelling

    1. Front Matter

      Pages 9-9
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    2. Graphical Regression

      • R. Dennis Cook
      Pages 11-22

    3. LAPACK: A Linear Algebra Library for High-Performance Computers

      • Jack J. Dongarra, James W. Demmel, Susan Ostrouchov
      Pages 23-28

    4. PARELLA: Measurement of Latent Attitude via the Statistical Modelling of Response Processes

      • Herbert Hoijtink
      Pages 29-34

    5. On Fitting Non-Stationary Markov Point Process Models on GLIM

      • A. B. Lawson
      Pages 35-40

    6. Measuring Departure from Gaussian Assumptions in Spatial Processes

      • D. Posa, M. Rossi
      Pages 41-46

    7. Monte Carlo Simulation on Software Mutation Test-Case Adequacy

      • Mehmet Sahinoglu, Ibrahim Baltaci, E. H. Spafford
      Pages 47-52

    8. Exploratory Analysis of Ordinal Repeated Measures

      • S. R. Wilson
      Pages 53-57

  4. Multivariate Analysis

    1. Front Matter

      Pages 59-59
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    2. Scaling Factors in Generalised Procrustes Analysis

      • G. M. Arnold
      Pages 61-66

    3. Correspondance Table between Two Sets, One Partitioned, and Associated Tables

      • P. Cazes, J. Moreau
      Pages 67-70

    4. DOMOUSE: Detection of Multivariate Outliers Using S Environment

      • Robert Cléroux, Jean-Marie Helbling, Normand Ranger
      Pages 71-75

    5. Algorithmic Approaches for Fitting Bilinear Models

      • A. de Falguerolles, B. Francis
      Pages 77-82

    6. Ordinal Principal Component Analysis

      • Pekka J. Korhonen, Aapo Siljamäki
      Pages 83-87

    7. Computational Procedures for Estimation and Hypothesis Testing in Analyzing Two-Way Tables with Interaction and No Replication

      • Mahmoud Seyedsadr, Paul L. Cornelius
      Pages 89-94

    8. Computational Aspects of the Nearest Neighbor Statistics

      • E. Trybus, G. Trybus
      Pages 95-100

  5. Classification and Discrimination

    1. Front Matter

      Pages 101-101
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Keywords

About this book

The Role of the Computer in Statistics David Cox Nuffield College, Oxford OXIINF, U.K. A classification of statistical problems via their computational demands hinges on four components (I) the amount and complexity of the data, (il) the specificity of the objectives of the analysis, (iii) the broad aspects of the approach to analysis, (ill) the conceptual, mathematical and numerical analytic complexity of the methods. Computational requi­ rements may be limiting in (I) and (ill), either through the need for special programming effort, or because of the difficulties of initial data management or because of the load of detailed analysis. The implications of modern computational developments for statistical work can be illustrated in the context of the study of specific probabilistic models, the development of general statistical theory, the design of investigations and the analysis of empirical data. While simulation is usually likely to be the most sensible way of investigating specific complex stochastic models, computerized algebra has an obvious role in the more analyti­ cal work. It seems likely that statistics and applied probability have made insufficient use of developments in numerical analysis associated more with classical applied mathematics, in particular in the solution of large systems of ordinary and partial differential equations, integral equations and integra-differential equations and for the ¢raction of "useful" in­ formation from integral transforms. Increasing emphasis on models incorporating specific subject-matter considerations is one route to bridging the gap between statistical ana.­

Editors and Affiliations

  • Groupe de Statistique, University of Neuchâtel, Neuchâtel, Switzerland

    Yadolah Dodge

  • Lancaster University, GB-Lancaster, Great Britain

    Joe Whittaker

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