Compstat

1. Front Matter

   Pages I-XIII

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2. Treatment of “Huge” Data Sets

   1. Front Matter

      Pages 1-1

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   2. Huge Data Sets

      • Peter J. Huber

      Pages 3-13

   3. Assessing Convergence of Markov Chain Monte Carlo Methods

      • Arnoldo Frigessi

      Pages 14-27

3. Numerical Analysis Useful in Statistics

   1. Front Matter

      Pages 29-29

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   2. What can Numerical Analysis do for Statistics?

      • Håkan Ekblom

      Pages 31-45

   3. Computation of Statistics Integrals using Subregion Adaptive Numerical Integration

      • Alan Genz

      Pages 46-51

   4. Universal Generators for Correlation Induction

      • Wolfgang Hörmann, Gerhard Derflinger

      Pages 52-57

   5. Local Polynomial Approximation of Rapidly Time-Varying Parameters of Nonlinear Dynamics

      • Vladimir Y. Katkovnik

      Pages 58-63

   6. Backfitting and Related Procedures for Non-parametric Smoothing Regression: A Comparative View

      • Michael G. Schimek, Gerhard P. Neubauer, Haro Stettner

      Pages 64-69

4. Parallel Statistical Computing

   1. Front Matter

      Pages 71-71

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   2. Parallelism in Computational Statistics

      • Herman J. Adèr

      Pages 73-78

5. Selection Procedures

   1. Front Matter

      Pages 79-79

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   2. Construction of Decision Procedures for Selecting Populations

      • Guido Giani

      Pages 81-93

6. Computational Aspects in Optimization

   1. Front Matter

      Pages 95-95

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   2. A New Robust Design Strategy for Sigmoidal Models Based on Model Nesting

      • Timothy E. O’Brien

      Pages 97-102

7. Computational Aspects in Spatial Statistics and GIS

   1. Front Matter

      Pages 103-103

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   2. Some Dynamic Graphics for Spatial Data (with Multiple Attributes) in a GIS

      • Dianne Cook, Noel Cressie, James Majure, Jürgen Symanzik

      Pages 105-119

   3. Stochastic Modelling of Spatial and Dynamic Patterns. Applications in Ecology

      • Hans-Peter Bäumer, Heidrun Ortleb, Dietmar Pfeifer, Ulrike Schleier-Langer

      Pages 120-125

8. Computational Aspects in Discrimination and Classification

   1. Front Matter

      Pages 127-127

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This book assembles papers which were presented at the biennial sympo­ sium in Computational Statistics held und er the a!uspices of the International Association for Statistical Computing (IASC), a section of ISI, the Interna­ tional Statistical Institute. This symposium named COMPSTAT '94 was organized by the Statistical Institutes of the University of Vienna and the University of Technology of Vienna, Austria. The series of COMPSTAT Symposia started 1974 in Vienna. Mean­ while they took place every other year in Berlin (Germany, 1976), Leiden (The Netherlands, 1978), Edinburgh (Great Britain, 1980), Toulouse (France, 1982), Prague (Czechoslovakia, 1984), Rom (Italy, 1986), Copenhagen (Den­ mark, 1988), Dubrovnik (Yugoslavia, 1990) and Neuchätel (Switzerland, 1992). This year we are celebrating the 20th anniversary in Vienna, Austria. It has obviously been observed a movement from "traditional" computa­ tional statistics with emphasis on methods which produce results quickly and reliably, to computationally intensive methods like resampling procedures, Bayesian methods, dynamic graphics, to very recent areas like neural net­ works, accentuation on spatial statistics, huge data sets, analysis strategies, etc. For the organization of the symposium, new guidelines worked out by the IASC in written form were in effect this time. The goal was to refresh somehow the spirit of the start of COMPSTAT '74, keep the tradition of the series and ensure a certain continuity in the sequence of biannual meetings.

• Datenanalyse
• Resampling
• Statistik
• Time series
• bayesian statistics
• computational statistics
• computergestützte Statistik
• data analysis
• information system
• modeling
• optimization
• simulation
• statistical software
• statistics

• Department for Statistics and Probability Theory, University of Technology Vienna, Vienna, Austria

  Rudolf Dutter

• Department of Statistics, OR and Computer Science, University Vienna, Vienna, Austria

  Wilfried Grossmann

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