This book is a collection of thirty invited papers, covering the important parts of a rapidly developing area like "computational statistics". All contributions supply information about a specialized topic in a tutorial and comprehensive style. Newest results and developments are discussed. Starting with the foundations of computational statistics, i.e. numerical reliability of software packages or construction principles for pseudorandom number generators, the volume includes design considerations on statistical programming languages and the basic issues of resampling techniques. Also covered are areas like design of experiments, graphical techniques, modelling and testing problems, a review of clustering algorithms, and concise discussions of regression trees or cognitive aspects of authoring systems.
Editorial.- The Roots of Computational Statistics in Germany.- Twenty-Five Working Conferences on Statistical Computing - Reflections on Twenty Years of Reisensburg Meetings.- Remarks on the History of Computational Statistics in Europe.- Languages for Statistics and Data Analysis.- A Brief History of S.- Practical Guidelines for Testing Statistical Software.- On the Choice and Implementation of Pseudorandom Number Generators.- Seven Stages of Bootstrap.- Special Resampling Techniques in Categorical Data Analysis.- Statistical Problems in Planning, Conduct and Analysis of Epidemiological Studies.- Computer Aided Design of Experiments.- Knowledge-Based Systems in Statistics: A Tutorial Overview with Examples.- Diagnostic Plots for One-Dimensional Data.- Graphical Data Analysis Using LISP-STAT.- Multivariate Graphics: Current Use and Implementations in the Social Sciences.- Interactive Analysis of Spatial Data.- REGARDing Geographic Data.- Applied Nonparametric Smoothing Techniques.- Missing Values: Statistical Theory and Computational Practice.- A Permutation Approach to Configural Frequency Analysis (CFA) and the Iterated Hypergeometric Distribution.- Dynamic Modelling of Discrete Data.- Evaluating the Significance Level of Goodness-of-Fit Statistics for Large Discrete Data.- A Multiple Test Procedure for Nested Systems of Hypotheses.- Kernel Estimation in the Proportional Hazards Model.- Interval Censored Observations in Clinical Trials.- Covariates in Clinical Trials: Effects of Adjustment in Regression Models.- Classification and Regression Trees (CART) Used for the Exploration of Prognostic Factors Measured on Different Scales.- Clustering Algorithms and Cluster Validation.- Learning Statistics: Beyond Authoring Systems.- Remarks on Protecting Patient Data Against Misuse and on its Consequences Concerning their Statistical Data Analysis.- Alphabetical List of Authors, Reviewers and Editors.- Acknowledgements.