Computational Statistics

Prologue.- Science, Data, Statistics and Computing.- I. Statistical Modelling.- Graphical Regression.- LAPACK: A Linear Algebra Library for High-Performance Computers.- PARELLA: Measurement of Latent Attitude via the Statistical Modelling of Response Processes.- On Fitting Non-Stationary Markov Point Process Models on GLIM.- Measuring Departure from Gaussian Assumptions in Spatial Processes.- Monte Carlo Simulation on Software Mutation Test-Case Adequacy.- Exploratory Analysis of Ordinal Repeated Measures.- II. Multivariate Analysis.- Scaling Factors in Generalised Procrustes Analysis.- Correspondance Table between Two Sets, One Partitioned, and Associated Tables.- DOMOUSE: Detection of Multivariate Outliers Using S Environment.- Algorithmic Approaches for Fitting Bilinear Models.- Ordinal Principal Component Analysis.- Computational Procedures for Estimation and Hypothesis Testing in Analyzing Two-Way Tables with Interaction and No Replication.- Computational Aspects of the Nearest Neighbor Statistics.- III. Classification and Discrimination.- Discrimination through the Regularized Nearest Cluster Method.- Segmentation Trees: A New Help Building Expert Systems and Neural Networks.- Classification by Quantification of Ranking Pattern.- Tree-Growing for the Multivariate Model: The RECPAM Approach.- On the Level of Regularization in Regularized Discriminant Analysis.- Additive Spline Discriminant Analysis.- A New Dynamic Programing Algorithm for Cluster Analysis.- StatLog: An Evaluation of Machine Learning and Statistical Algorithms.- Discriminant Analysis of Plasma Fusion Data.- Presentation of the Method of Density Slices: An Answer to the Multitendencies Problems.- A Two-Stage Predictive Splitting Algorithm in Binary Segmentation.- A Comparative Study of Two Methods ofDiscrete Regularized Discriminant Analysis.- IV. Symbolic and Relational Data.- From Data to Knowledge: Probabilist Objects for a Symbolic Data Analysis.- Comparing Numerical and Symbolic Clustering: Application to Pseudoperiodic Light Curves of Stars.- Description of a Knowledge Base of Symbolic Objects by Histograms.- An Efficient Neural Network by a Classification Tree.- V. Graphical Models.- Graphical Models for Dependencies and Associations.- Model Search in Contingency Tables by CoCo.- Stochastic Simulation in Mixed Graphical Association Models.- Recognizing Submodels of a Loglinear Model.- HModel: An X Tool for Global Model Search.- Assessing the Power of Model Selection Procedures used when Graphical Modelling.- VI. Time Series Models.- Computing Missing Values in Time Series.- Forecasting Singapore's GDP Growth with a Small-Scale Model.- Construction of State Space Models for Time Series Exhibiting Exponential Growth.- The Technique of ?-Transformation in Econometric Data Series.- Econometric Modelling on Micro-Computers: The Impact of the New Technological Features.- Two New Robust Methods for Time Series.- Forecasting Using a Semiparametric Model.- Computing ARMA Models with MATLAB.- Analyzing Treatment Effects - The WAMASTEX Approach to Paired Sample Data.- Fortune: Improving Forecasts by Tuning the Forecasting Process.- A Comparative Study of Outlier Detection and Missing Value Estimation Methods Applied to Time Series Transport Data.- Linking Judgements to Forecasting Models.- Numerical Computation of Exact Distributions for First Order Stochastic Difference Equations.- VII. Nonlinear Regression.- Estimation of Radioimmunoassay Data Using Robust Nonlinear Regression Methods.- An Artificial Intelligence Approach for Modeling in Nonlinear RegressionParametric Models.- Accurate Multivariable Numerical Derivatives for Inference in Nonlinear Regression.- Advantages of the Approximative Interpretation - An Algorithm and Program for Finding Solutions of Large Non-Linear Problems.- Providing for the Analysis of Generalized Additive Models within a System already Capable of Generalized Linear and Nonlinear Regression.- A Note on Local Sensitivity of Regression Estimates.- Parallel Model Analysis with Factorial Parameter Structure.- VIII. Robustness and Smoothing Techniques.- Time-Efficient Algorithms for Two Highly Robust Estimators of Scale.- Universal Consistency of Partitioning-Estimates of a Regression Function for Randomly Missing Data.- The Use of Slices in the LMS and the Method of Density Slices: Foundation and Comparison.- On Some Statistical Properties of Bézier Curves.- Trade Regression.- A Review on Smoothing Methods for the Estimation of the Hazard Rate Based on Kernel Functions.- Departures from Assumptions in Two-Phase Regression.- An Analysis of the Least Median of Squares Regression Problem.- Nonparametric Regression Methods for Smoothing Curves.- An Inference Procedure for the Minimum Sum of Absolute Errors Regression.- An Operator Method for Backfitting with Smoothing Splines in Additive Models.- Sensitivity Analysis in Structural Equation Models.- Methods for Robust Non-Linear Regression.- IX. Industrial Applications: Pharmaceutics and Quality Control.- Statistical Thinking in Total Quality Management: Implications for Improvement of Quality - with Ideas for Software Development.- Statistical Computation in the Pharmaceutical Industry.- Stochastic Simulations of Population Variability in Pharmacokinetics.- Computational Aspects in Uncertainty Analyses of Physiologically-Based PharmacokineticModels.- X. Bayesian Statistics.- Simulated Annealing in Bayesian Decision Theory.- Generalized Linear Models and Jeffreys Priors: An Iterative Weighted Least-Squares Approach.- Approaches to Tobit Models via Gibbs Sampling.- Bayesian Predictive Screening: An Efficient Approach for the Multivariate Binary, Ordinal Responses.- Author Index.- Table of Contents of Volume Two.- Author Index of Volume Two.