edited by Peter Brown (University of Canberra), Shuangzhe Liu (University of Canberra), & Dharmendra Sharma (University of Canberra)

Table of Contents (75k)
Preface (57k)
Chapter 1: Estimating Internet Access for Welfare Recipients in Australia (110k)

Contributed by world renowned researchers, the book features a wide range of important topics in modern statistical theory and methodology, economics and finance, ecology, education, health and sports studies, and computer and IT-data mining. It is accessible to students and of interest to experts.

Many of the contributions are concerned with theoretical innovations, but all have applications in view, and some contain illustrations of the applied methods or photos of historic mathematicians.

A few of the notable contributors are Ejaz Ahmed (Windsor), Joe Gani (ANU), Roger Gay (Monash), Atsuhiro Hayashi (NCUEE, Tokyo), Markus Hegland (ANU), Chris Heyde (ANU/Columbia), Jeff Hunter (Massey), Phil Lewis (Canberra), Heinz Neudecker (Amsterdam), Graham Pollard (Canberra), Simo Puntanen (Tampere), George Styan (McGill), and Goetz Trenkler (Dortmund).

• Mathematics and Statistics in Society:
  • Two Classification Methods of Individuals for Educational Data and an Application (A Hayashi)
  • Measurement of Skill and Skill Change (R Kelly & P E T Lewis)
• Applications of Statistics:
  • Estimating the Numbers of SARS Cases in Mainland China in 2002-3 (J Gani)
  • A Fair Tennis Scoring System for Doubles in the Presence of Sun and Wind Effects — An Application of Probability (G Pollard)
• Theoretical Issues in Probability and Statistics:
  • Perturbed Markov Chains (J J Hunter)
  • Matrix Tricks for Linear Statistical Models: A Short Review of Our Personal Top Fourteen (J Isotalo et al.)
  • On the Approximate Variance of a Nonlinear Function of Random Variables (H Neudecker & G Trenkler)
• Probabilistic Models in Economics and Finance:
  • When Large Claims are Extremes (R Gay)
  • Shrinkage Estimation of Gini Index (R Ghori et al.)
• Numerical Methods:
  • An Approximate Maximum a Posteriori Method with Gaussian Process Priors (M Hegland)
  • Mining Multiple Models (G J Williams)
• Abstracts Without Papers:
  • Properties of Nearest-Neighbour Classifiers (P Hall)
  • Bootstrapping in Clustered Populations (A H Welsh)
  • and other papers