COMPSTAT : proceedings in computational statistics, 11th symposium held in Vienna, Austria, 1994
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COMPSTAT : proceedings in computational statistics, 11th symposium held in Vienna, Austria, 1994
Physica-Verlag, 1994
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COMPSTAT 1994
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Includes bibliographical references and index
Description and Table of Contents
Description
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 Neuchatel (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.
Table of Contents
- Part 1 Computation and algorithms: treatment of "huge" data sets
- parallel statistical computing
- computational aspects in optimization
- neural networks
- metadata and statistical information systems
- evaluation and comparison of statistical software. Part 2 Statistical inference and design: selection procedures
- Bayesian statistics
- sequential analysis and quality control
- reliability and survival
- robustness
- time series
- resampling methods
- experimental design. Part 3 statistical modelling: sptial statistics and GIS
- discrimination and classification and multivariate analysis.
by "Nielsen BookData"