Short Book Reviews

Vol. 24. No. 3 — December 2004 Editor Dr. A.M. Herzberg

REVIEWS THE THIRD MAN OF THE DOUBLE HELIX.

M. Wilkins. Oxford University Press: 2003, pp. xiv + 274, £16.99.

Contents:

1. Distant Shores 2. Finding my feet 3. In a world at war 4. Randall's circus 5. Crystal genes 6. Go back to your microscopes 7. How does DNA keep its secrets? 8. The double helix 9. Living with the double helix

10. A broader view Readership: Anyone interested in the origins of molecular

biology and the modern bioinformatic, genomic, and protemic revolution, and in the history of a controversial episode in science

This is the autobiography of Maurice Wilkins, who

shared the 1962 Nobel Prize in physiology or medicine with Francis Crick and James Watson for the discovery of the structure of DNA.

Much has been written about the role of Rosalind Franklin in the discovery of DNA. Wilkins and she did not always get on very well, and there has been controversy about the way her contribution was treated. Wilkins writes '[Jim Watson's book The Double Helix] enabled some activists to mount a campaign in Rosalind's name to improve the lot of women in science. This was no doubt well intentioned and indeed useful, but one side-effect was that Rosalind's male colleagues were to some extent demonized. The most prominent demon seemed to be me. Since then, the Franklin/Wilkins story has often been told as an example of the unjustness of male scientists towards their women colleagues, and questions have been raised over whether credit was distributed fairly when the Nobel Prize was awarded. I have found this situation distressing over the years, and I expect this book is in some way my attempt to respond to these questions, and to tell my side of that story.'

He also writes: 'The later years of my career have been devoted to the exploration of the social issues raised by advances in science. I believe that the tensions in the DNA story may shed some light on how tensions in other spheres might be avoided or addressed.'

Maurice Wilkins died on 5th October 2004. Imperial College of Science,

Technology and Medicine London, U.K. D.J. Hand

MEASURING INTELLIGENCE: FACTS AND FALLACIES.D.J. Bartholomew. Cambridge University Press, 2004, pp. xiv + 172, £40.00/US$70.00 Cloth; £15.99/US$24.99 Paper.

Contents:

1. The great intelligence debate: science or ideology? 2. Origins 3. The end of IQ 4. First steps to g5. Second steps to g6. Extracting g7. Factor analysis or principaI components analysis 8. One intelligence or many? 9. The Bell Curve: facts, fallacies, and speculations

10. What is g?11. Are some groups more intelligent than others? 12. Is intelligence inherited? 13. Facts and fallacies

Readership: Anyone interested in measuring intelligence or

the debate about what intelligence is

Vast amounts have been written about the nature of intelligence and whether and how it can be measured. The issue has been one of great controversy and polemics have been written on all sides.

The measurement of intelligence has always been closely bound up with statistical ideas. UnfortunateIy, not all of the discussants have had a clear grasp of these statistical concepts. Moreover, for good historical reasons, early work on some of the statistical tools was itself controversial ― though more recent developments have led to deeper understanding which has effectively resolved those statistical controversies. Regrettably not all of the commentators seem aware of these developments. In this book David Bartholomew sets the issues in the context of his seminal work on social measurement. He describes how the main single (latent) dimension of variation in human mental abilities can be measured in terms of manifest test variables, and distinguishes between this and IQ. Within the context of his model he examines the various controversies which have dogged discussions of measuring intelligence.

This book represents a step forward in the debate on measuring intelligence. It is essential reading for anyone concerned with the 'intelligence debate'. It will also make excellent reading for anyone learning about factor analysis, and provides a perfect illustration of the Bartholomew school of measurement models. Imperial College of Science,

Technology and Medicine London, U.K. D.J. Hand

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STATISTIQUE. LA THÉORIE ET SES APPLICATIONS.M. Lejeune. Paris: Springer-Verlag, 2004, pp. xiii + 339, €40.71/CHF74.50/US$38.27/£31.50.

Table des matières:

1. Variables aléatoires 2. Espérance mathématique et moments 3. Couples et n-uplets de variables aléatoires 4. Les lois de probabilités usuelles 5. Lois fondamentales de l'échantillonnage 6. Théorie de l'estimation paramétrique ponctuelle 7. Estimation paramétrique par intervalle de confiance 8. Estimation non paramétrique et estimation fonctionelle 9. Tests d'hypothèses paramétriques

10. Tests pour variables catégorielles et tests non paramétriques

11. Régressions linéaire, logistique et non paramétrique Lecture: Etudiants et professeurs du premier cycle en

sciences et sciences appliquées

La théorie des probabilités est introduite sans faire usage de la théorie de la mesure, ce qui fait que le livre est accessible à un public assez large. Les thèmes de la statistique sont classiques: estimation ponctuelle, intervalles de confiance, tests d'hypothèses, régression linéaire. Mais on parle aussi de l'estimation non paramétrique (de la densité, des quantiles, de la fonction de régression) et des tests non paramétriques. La lecture, présuppose une certaine connaissance de mathématiques pour comprendre les démonstrations mais elle reste ouverte à un très grand nombre d'étudiants. Intéressant comme manuel pour l'enseignement est que chaque chapitre se termine par une collection d'exercises, dont les plus difficiles ont un astérisque. Limburgs Universitair Centrum Diepenbeek, Belgium N.D.C. Veraverbeke

COGWHEELS OF THE MIND. THE STORY OF VENN DIAGRAMS.A.W.F. Edwards. Foreword by I. Stewart. Baltimore: Johns Hopkins University Press, 2004, pp. xvi + 110, £17.00.

Contents:

1. John Venn and his logic diagram 2. Rings, flags and balls 3. Five and more sets 4. The Gray Code, binomial coefficients and the

Revolving-Door algorithm 5. Cosine curves and sine curves 6. Ironing the hypercube 7. Diagrams with rotational symmetry

APPENDIX 1: Metrical Venn Diagrams APPENDIX 2: A Rotatable Edwards-Venn Diagram Readership: General readership, historians of mathematics

This book is a delight! Most school students meet the idea of a Venn

diagram to help with probability calculations involving three events: these conveniently involve intersecting congruent circles. When there are more than three events, the question of the Venn diagram construction using closed curves, let alone bounding symmetrical shapes, is much more challenging.

This book describes the development of Venn's ideas from the late nineteenth century to what are recent results. The illustrations are excellent and many are beautiful. The technical mathematical detail is kept to a minimum.

The author, like John Venn before him, is a Fellow of Gonville and Caius College, Cambridge. His

interest in Venn' s work and the way it has been developed gives an illuminating account of how research in mathematics is actually done and the excitement of discovering comes across very well. This makes the book ideal for motivation of budding, as well as active, mathematicians and an excellent and attractive addition to bookshelves.

If I were to have a favourite it is the construction of complex Venn Diagrams on a spherical surface to create 'Vennis Balls'. Imperial College of Science,

Technology and Medicine London, U.K. F.H. Berkshire

BEYOND REASON: 8 GREAT PROBLEMS THAT REVEAL THE LIMIT OF SCIENCE.A.K. Dewdney. Hoboken, New Jersey: Wiley, 2004, pp. 224, £19.99.

Contents:

Introduction: Where reason cannot go 1. The energy drain: lmpossible machines 2. The cosmic limit: Unreachable speeds 3. The quantum curtain: Unknowable particles 4. The edge of chaos: Unpredictable systems 5. The circular crypt: Unconstructable figures 6. The chains of reason: Unprovable theorems 7. The computer treadmill: Impossible programs 8. The Big-O bottleneck: Intractable problems

Readership: General

In the words of the author this book "provides a mind bending exploration not into what is doable and knowable ― but what is undoable and unknowable".

As can be seen from the chapter headings the concentration here is on apparently permanent barriers, rather than those which might be overcome in due course as knowledge and technology advance. Of course it is difficult to define the barriers as absolute, but this is an entertaining account for the general reader of the pros and cons as they appear today, together with an account of how our views have evolved.

The author has written several very popular mathematics/science books [including A Mathematical Mystery Tour, Yes We Have No Neutrons, 200% of Noth-ing] and was Computer Recreations columnist for Scientific American Magazine for eight years.

As a result the style of this book is appropriate for a general readership and it should prove as popular as his other books. Imperial College of Science,

Technology and Medicine London, U.K. F.H. Berkshire

A FIRST COURSE IN COMBINATORIAL OPTIMIZATION.J. Lee. Cambridge University Press, 2004, pp. xvi + 211, £60.00/US$90.00 Cloth; £20.99/US$32 Paper.

Contents:

Introduction 0. Polytopes and linear programming 1. Matroids and the greedy algorithm 2. Minimum-weight dipaths 3. Matroid intersection 4. Matching 5. Flows and cuts 6. Cutting planes 7. Branch-and-bound 8. Optimizing submodular functions

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Readership: Operational researchers, mathematicians, mathematical programmers

The text is designed to be a graduate introduction

to combinatorial optimization. It is concerned with the mathematics of the subject; there is only passing mention of applications, nothing about implementation, or sophisti-cated algorithms that have provable good lower bounds on the number of steps involved. The author, with his Iight but rigorous mathematical writing style, takes delight in re-veaIing the stars of combinatorial optimization. The reader does need some mathematical skills, a little knowledge of graph theory concepts, and linear programming. This is an excellent teaching book; I recommend it highly. My regret is that I cannot use it this year as l am not teaching the combinatorial optimization course.

London School of Economics London, U.K. S. Powell

STATISTICS AND THE EVALUATION OF EVIDENCE FOR FORENSIC SCIENTISTS, 2nd edition. C.C. Aitken and F. Taroni. Chichester, U.K.: Wiley, 2004, pp. xxx + 509, £65.00.

Contents:

1. Uncertainty in forensic science 2. Variation 3. The evaluation of evidence 4. Historical review 5. Bayesian inference 6. Sampling 7. Interpretation 8. Transfer evidence 9. Discrete data

10. Continuous data 11. Multivariate analysis 12. Fibres 13. DNA profiling 14. Bayesian networks

Readership: Forensic scientists, lawyers, teachers and

students of statistics seeking interesting applications

Those familiar with the first edition [Short Book

Reviews, Vol. 15, p. 41] will notice that the total length has now doubled, as has that of the bibliography. Indeed the number of authors has also doubled, with Franco Taroni joining Colin Aitken, and contributing particularly on the history and philosophy of inference in forensic science, European legal systems, and Bayesian networks.

The doubling in size reflects both coverage of new topics and the explosive growth of the field. There are six new chapters, on Bayesian inference, Sampling, Interpretation, Multivariate Analysis, Fibres and Bayesian Networks. Even now, the book is not exhaustive on applications of statistics to the law, but primarily treats transfer evidence linking a suspected offender with a crime scene. Forensic statistics associated with civil, rather than criminal, cases are not covered, for example regression modelling to establish causation, or discrimination, or to estimate economic Iosses.

The coverage of transfer evidence is, however, wide-ranging and authoritative, including extensive references to the literature. As well as the chapters devoted to DNA profiles and fibres, the evidence types covered include glass, earprints, fingerprints, handwriting, speaker recognition, and paint, among others. A nice feature of the present book is its brief forays into historical context, discussing for example statistical aspects of the infamous C19 French Dreyfus case, the C20 California Collins case that inspired much of the modern academic literature on interpretation of identification evidence. DNA evidence is now a huge field in its own right; the present authors provide a useful introduction, that has been

substantially improved and updated since the first edition, but it cannot match the exhaustive treatment of a dedicated book such as that of BuckIeton, Triggs and Walsh (CRC Press, 2004).

The statistical methods discussed are for the most part elementary. There is an introduction to probabil-ity, some sampling theory, coverage of some key distribu-tions, and introductions to likelihood and odds ratios, and Bayesian inference. Two more advanced topics have their own dedicated chapters near the end of the book: multi-variate analysis and Bayesian networks. The difficult part of the subject is not how to implement any particular statis-tical technique, but how to formulate appropriate hypothe-ses and to interpret the statistical results in the context of these. Appropriately, the authors have given considerable attention to these tricky questions of interpretation, includ-ing a discussion of common errors and fallacies. Imperial College of Science,

Technology and Medicine London, U.K. D.J. Balding

ENVIRONMENTAL STATISTICS METHODS AND APPLICATIONS.V. Barnett. Chichester, U.K.: Wiley, 2004, pp. xi + 293, £55.00.

Contents:

1. Introduction PART I: Extremal Stresses: Extremes, Outliers,

Robustness 2. Ordering and extremes: Applications, models,

inference 3. Outliers and robustness

PART II: Collecting Environmental Data: Sampling and Monitoring

4. Finite-population sampling 5. Inaccessible and sensitive data 6. Sampling in the wild

PART III: Examining Environmental Effects: Stimulus-Response Relationships

7. Relationship: Regression-type models and method 8. Special relationship models, including quantal

response and repeated measures PART IV: Standards and Regulations

9. Environmental standards PART V: A Many-Dimensional Environment: Spatial and

Temporal Processes 10. Time-series methods 11. Spatial methods for environmental processes

Readership: Statisticians, environmental scientists and

environmental engineers

This book brings together a wide range of statistical ideas, concepts and methods relating to environmental research, that formally have been dispersed throughout the literature. The text is well written and the methods are illustrated with interesting examples. Following an introductory chapter describing the kinds of applications considered and the basic concepts and definitions, the author considers the material in five parts. The first is on order-statistics and extreme-value distributions, the identification of outliers, the concept of robust estimation and the accommodation of influential observations. Part two is on sampling methods, beginning with the basic ideas of simple random and stratified sampling applied to finite populations, but also referring to specific methods such as random-set sampling, capture-recapture methods and transect sampling. Part three covers modelling using basic regression analysis, generalized linear models and quantal response models. This is followed by an interesting chapter on the maintenance of environmental standards, set up to control the exposure levels of pollutants or contaminants. The final

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part brings us right up to date with a description of spatial and temporal models, including time-domain models, frequency-domain models, point and spatial processes, with spatial-temporal models described briefly in the last chapter. The book covers a wealth of statistical concepts as applied to the environment, giving a general overview of the methods developed over many years. One of its main features is that it provides a comprehensive reference source for anyone working on environmental issues. University of Southampton Southampton, U.K. P. Prescott

APPLIED BAYESIAN MODELING AND CAUSAL INFERENCE FROM INCOMPLETE-DATA PERSPECTIVES.A. Gelman and X.-L. Meng (Eds.). Chichester, U.K.: Wiley, 2004, pp. xix + 407, £55.00.

Contents: PART I: Causal Inference and Observational Studies

1. An overview of methods for causal inference from observational studies

2. Matching in observational studies 3. Estimating causal effects in nonexperimental studies 4. Medication cost sharing and drug spending in

Medicare 5. A comparison of experimental and observational data

analysis 6. Fixing broken experiments using the propensity score 7. The propensity score with continuous treatments 8. Causal inference with instrumental variables 9. Principal stratification

PART II: Missing Data Modeling 10. Nonresponse adjustment in government statistical

agencies: Constraints, inferential goals, and robustness issues

11. Bridging across changes in classification systems 12. Representing the Census undercount by multiple

imputation 13. Statistical disclosure techniques based on multiple

imputation 14. Designs producing balanced missing data: examples

from the National Assessment of Educational Progress

15. Propensity score estimation with missing data 16. Sensitivity to nonignorability in frequentist inferences

PART III: Statistical Modeling and Computation 17. Statistical modeling and computation 18. Treatment effects in before-after data 19. Multimodality in mixture models and factor models 20. Modeling the covariance and correlation matrix of

repeated measures 21. Robit regression: A simple robust alternative to logistic

and probit regression 22. Using EM and data augmentation for the competing

risks model 23. Mixed effects models and the EM algorithm 24. The sampling/importance resampling algorithm

PART IV: Applied Bayesian Inference 25. Whither applied Bayesian inference? 26. Efficient EM type algorithms for fitting spectral lines in

high-energy astrophysics 27. Improved predictions of lynx trappings using a

biological model 28. Record linkage using finite mixture models 29. Identifying likely duplicates by record linkage in a

survey of prostitutes 30. Applying structural equation models with incomplete

data 31. Perceptual scaling

Readership: Academic (Statistics: researchers and practitioners)

This is a collection of articles in a volume dedi-

cated to Professor D. Rubin for his sixtieth birthday. As will be seen from the Contents, the book is divided into four parts, each beginning with an overview of the area. (Inci-dentally, is it really 'Casual Inference' on pages xiii and 1?)

The issues covered here are missing data, modelling, computation, causal mechanisms, are pervasive in Statistics; also, the application areas are wide-ranging. That said, the 'Rubin Statistical Family Tree' reveals the close connection of most of the authors with Professor Rubin: of the thirty-one chapters, twenty-four have authors who were his students, or students of his students. This gives the book a certain flavour, which will be seen by some as a justifiable unifying theme.

I believe that the book will be a very useful addition to academic libraries. Students (and professors) will be able to look up and learn about particular areas, rather than reading it from cover to cover.

Imperial College of Science,

Technology and Medicine London, U.K. M.J. Crowder

KENDALL'S ADVANCED THEORY OF STATISTICS,2nd edition, Volume 2B: Bayesian Inference. A. O'Hagan and J. Forster. London: Arnold, 2004, pp. xiii + 480.

Contents:

1. The Bayesian method 2. Inference and decisions 3. General principles and theory 4. Subjective probability 5. Non-subjective theories 6. Subjective prior distributions 7. Model comparison 8. Robustness and model criticism 9. Computation

10. Markov chain Monte Carlo 11. The linear model 12. Discrete data models 13. Nonparametric models 14. Other standard models 15. Short case studies

Readership: Academic (researchers, practitioners,

students); industry and commerce (statistics practitioners)

First, as well as an extra author (Forster now

joins the original one, O'Hagan), there is much additional material in this second edition: the old Chapter 7 is now Chapters 7 and 8; the old Chapter 8 is now Chapters 9 and 10; the old Chapter 9 is now Chapter 11, now supple-mented by a new chapter, Chapter 12; the old Chapter 10 is now Chapter 14; there are new chapters, Chapter 13 and Chapter 15.

Regarding the philosophy of inference, the authors cannot be accused of sitting on the fence. For example, they say in Section 1.33 that, "It is not surprising that a method [Bayesian] which is fundamentally superior [to the Frequentist Approach], and in particular which makes use of more information, requires more effort to implement". I might argue with the use of "which" here, instead of "that", but I'm sure others would argue more substantially.

As one would expect from these authors the book provides an authoritative, up-to-date, comprehensive ac-

45

count of both Bayesian theory and practicalities. There is much explanation and discussion, which will well serve re-searchers, practitioners and students. There are plenty of examples and exercises, and the reference list and index are both extensive. Finally, as with the other tomes in the series, the whole is regimented into bite-size, numbered sections for ease of digestion and reference. Imperial College of Science,

Technology and Medicine London, U.K. M.J. Crowder

STATISTICAL MODELS.A.C. Davison. Cambridge University Press, 2003, pp. x + 726, £40.00.

Contents:

1. Introduction 2. Variation 3. Uncertainty 4. Likelihood 5. Models 6. Stochastic models 7. Estimation and hypothesis testing 8. Linear regression models 9. Designed experiments

10. Nonlinear regression models 11. Bayesian models 12. Conditional and marginal inference

APPENDIX: Practicals Readership: Practitioners and researchers in applied and

theoretical statistics, from postgraduate level upwards

The concept of an underlying model is funda-

mental to much statistical thinking today. Here Anthony Davison takes this as the focus for an almost encyclopae-dic survey of modern parametric statistics. In my view this mammoth and scholarly undertaking invites comparison with Kendall's original Advanced Theory of Statistics, pro-viding as it does a snapshot of the discipline at the present time. 'Classical' material is presented side by side with re-cent developments including graphical models, extreme value models, robust estimation and computational tech-niques. The exposition avoids undue technicality, but indi-cates the nature of technical requirements where neces-sary. There are plenty of examples and exercises, many of which will be suitable for teaching purposes. An accompa-nying library of online sets of data is promised, although as of June 2004 this does not appear to have materialized. Marginal notes provide a mix of historical background in-formation and entertainment. Anybody who is seriously in-volved in the theory or practice of statistics would be well advised to ensure that they have access to a copy. University College London London, U.K. R.E. Chandler

THE KERNAL METHOD OF TEST EQUATING.A.A. von Davier, P.W. Holland and D.T. Thayer. New York: Springer-Verlag, pp. xxii + 229, US$69.95.

Contents:

1. Introduction and notation 2. Data collection designs 3. Kernal equating: Overview, pre-smoothing, and

estimation of r and s 4. Kernal equating: Continuization and equating 5. Kernal equating: The SEE and the SEED 6. Kernal equating versus other equating methods 7. The equivalent groups design

8. The single group design 9. The counterbalanced design

10. The NEAT design: Chain equating 11. The NEAT design: Post-stratification equating

APPENDIX A: The delta method APPENDIX B: Bivariate smoothing APPENDIX C: Other univariate moments APPENDIX D: Review of the use of matrices in this book Readership: Those who make, evaluate, and compare

tests

All three authors work at the Educational Testing Service in Princeton, New Jersey. Their joint opus is a specialized book about research and practice in the field of test equating, which arises from the need to be able to produce tests that can be consistently interpreted over many groups of students who may or may not have answered the exact same questions, at the same or different times.

Chapters 2-6 present the theory; applications follow in Chapters 7-11. The book is nicely laid out, is ex-tremely well written, and is an excellent text for a semester course or a short course. There are sixty-three diagrams and seventy-two references. The book is highly recom-mended. University of Wisconsin Madison, U.S.A. N.R. Draper

MULTIVARIATE t-DISTRIBUTIONS AND THEIR APPLICATIONS.S. Kotz and S. Nadarajah. Cambridge University Press, 2004, pp. xii + 272, £45.00/US$65.00.

Contents:

1. Introduction 2. The characteristic function 3. Linear combinations, products, and ratios 4. Bivariate generalizations and related distributions 5. Mutivariate generalizations and related distributions 6. Probability integrals 7. Probability inequalities 8. Percentage points 9. Sampling distributions

10. Estimation 11. Regression models 12. Applications

Readership: Statisticians interested in continuous

multivariate distribution theory, analysis and applications

This monograph is the latest publication to

concentrate on a narrow class of very closely related distributions and to examine it in great detail from various aspects. The authors believe that the multivariate t-distributions have been somewhat overshadowed by the multivariate normal, although they provide a more viable alternative for handling real data and are widely used in Bayesian analysis of multivariate data. Their aim was "to collect and present in an organized and user-friendly manner all of the relevant information available in the literature worthy of publication". The first part of the book is mainly devoted to distribution theory; the second is more concerned with estimation and applications. There are about 400 references in the bibliography. The general style and mathematical level are similar to that of Continuous Multivariate Distributions, 1, 2nd edition (2000), S. Kotz, N. Balakrishnan, and N.L. Johnson, Wiley [Short BookReviews, Vol. 20, p. 41]. University of St. Andrews St. Andrews, U.K. C.D. Kemp

46

AN INTRODUCTION TO MODERN NONPARAMETRIC STATISTICS.J.J. Higgins. Pacific Grove, California: Thomson Brooks/Cole, pp. xviii + 366.

Contents:

0. Preliminaries 1. One-sample methods 2. Two-sample methods 3. K-sample methods 4. Paired comparisons and blocked designs 5. Tests for trends and association 6. Multivariate tests 7. Analysis of censored data 8. Nonparametric bootstrap methods 9. Multifactor experiments

10. Smoothing methods and robust model fitting Readership: Students

The author assumes that readers have an introductory statistics course as background knowledge. The text is plainly but attractively set, the writing is nicely conversational and extremely clear. Four computer packages are featured: Resampling Stats, StatXact, S-Plus and MINITAB. The many sets of data throughout vary from real sets of data (attributed, with references), through sets made up or generated but based on experimental ideas (e.g., battery lifetimes), to ones that appear to be simply made up. The balance of these is reasonable. There are a few diagrams and one hundred and three references. The book would be an excellent choice for self-study or for a one-semester course. University of Wisconsin Madison, U.S.A. N.R. Draper NONPARAMETRIC AND SEMIPARAMETRIC MODELS.

W. Härdle, M. Müller, S. Sperlich and A. Werwatz. Berlin: Springer-Verlag, 2004, pp. xxvii + 299, US$88.95.

Contents:

1. lntroduction 2. Histogram 3. Nonparametric density estimation 4. Nonparametric regression 5. Semiparametric and generalized regression models 6. Single index models 7. Generalized partial linear models 8. Additive models and marginal effects 9. Generalized additive models

Readership: Undergraduate and first-year graduate

statistics, mathematics, econometrics and biostatistics students; graduate students, researchers

The book is a downloadable e-book; see www.i-

xplore.de. The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties. Difficulties are raised at the end of each chapter, and these motivate the development of improvements in the following chapter. There are only a few exercises, and they are typically of a technical nature. The only disappointment is that there is virtually no reference to computing. The illustrations are based on data in references, and it would be very difficult for someone to check the numbers or calibrate their own computations. Discussions on where to find software to implement the methods are needed. Pennsylvania State University University Park, U.S.A. T.P. Hettmansperger

INTRODUCTION TO REGRESSION ANALYSIS.M.A. Golberg and H.A. Cho. Southampton, U.K.: WIT Press, 2004, pp. x + 436, US$195.00.

Contents:

1. Introduction 2. Some basic results in probability and statistics 3. Simple linear regression 4. Random vectors and matrix algebra 5. Multiple regression 6. Residuals, diagnostics and transformations 7. Further applications of regression techniques 8. Selection of a regression model 9. Multicollinearity: diagnosis and remedies

Readership: Scientists of aII Ievels needing advanced

statistical data analysis and modeling On page 1, this book is described by "in contrast

to other books on this topic [27, 87], we have attempted to provide details of the theory rather than just presenting computational and interpretive aspects." I take exception to the word "just" in this context, because [27] is N.R. Draper and H. Smith's Applied Regression Analysis, 3rd edition, 1998, published by Wiley [Short Book Reviews, Vol. 19, p. 5]. The book [87] is Introduction to Linear Regression Analysis, 3rd edition, 2001, by D. Montgomery, E. Peck and G. Vining.

In the text under review, a lot of mathematical work is added to the regression analyses of data, and the result is a rather uneven presentation which, I think, will please few students. The authors suggest taking two semesters over the material unless some prior knowledge can be assumed.

I was surprised to find several instances of plagiarism of material taken from my own and Harry Smith's book. Parts of their pages 1 and 2 come from our page 45. The data on pages 317 and 319, 320 and 321 come from our pages 314 and 317. Their exercise 7.3 is from our exercise 14C. Their exercise 8.1 is from our exercise 15D. There is no indication at all that their sources are copyrighted.

The list price given inside the front cover is US$195.00 for 436 pages. This per page charge of 45 cents is high, compared with the 16 and 15 cents of the other books mentioned.

This book cannot be recommended.

University of Wisconsin Wisconsin, Madison N.R. Draper

ANALYSIS OF VARIANCE FOR RANDOM MODELS:Volume I, Balanced Data: Theory, Methods, Applications and Data Analysis. H. Sahai and M.M. Ojeda. Boston: Birkhäuser, 2004, pp. xxv + 484.

Contents:

1. Introduction 2. One-way classification 3. Two-way crossed classification without interaction 4. Two-way crossed classification with interaction 5. Three-way and higher crossed classifications 6. Two-way nested classification 7. Three-way and higher nested classifications 8. General balanced random effects model

Readership: Statisticians and experimentalists who use

analysis of variance to develop random effects models.

47

This is Volume I, covering balanced data, of a two-volume work on the analysis of variance used to develop random effects models. The theory and practice of fitting models, where all effects are considered to be random, are discussed in considerable detail for a wide range of experimental situations involving one, two or three factors, including both crossed and nested designs. Following a brief introduction used to elucidate in a unified way the basic results for the random effects analysis of variance, the authors cover, in subsequent chapters, the theory associated with models of increasing complexity, beginning with the simple one-way classification and ending with a description of the general balanced random effects model. Within each chapter for each model, the distribution theory of a variety of classical estimators such as ML, REML, MVU, Stein-type, Naqvi goodness of fit and Hodges-Lehmann-type estimators, is described and these estimators are illustrated with a numerical example supported by computer output derived from SAS, SPSS and BMDP. Bayesian estimators are also considered. The sampling distributions of the estimators of the variance components are covered at length, and confidence intervals and test procedures are developed for the variance components and selected functions of them. This text will provide a useful reference source for theoretical results and practical examples since each chapter is further supported by a comprehensive set of exercises and an extensive reference list.

University of Southampton, Southampton, U.K. P. Prescott

EXPLORING MULTIVARIATE DATA WITH THE FORWARD SEARCH.A.C. Atkinson, M. Riani and A. Cerioli. New York: Springer-Verlag, 2004, pp. xxi + 621, US$84.95.

Contents:

1. Examples of multivariate data 2. Multivariate data and the forward search 3. Data from one multivariate distribution 4. Multivariate transformations to normality 5. Principal components analysis 6. Discriminant analysis 7. Cluster analysis 8. Spatial linear models

APPENDIX: Tables of Data Readership: Advanced students of statistics, experimental

scientists, statisticians

This book is a companion to Atkinson and Riani (2000, Robust Diagnostic Regression Analysis) [ShortBook Reviews, Vol. 21, p. 4]. The idea of the forward search is first of all to identify a subset of the data that is free of outliers; as the search progresses, additional data points are added, and the effect is monitored graphically through appropriate plots, often involving Mahalanobis distances. The objective is to identify outliers, appreciate their influence and if possible discover a data transforma-tion which would result in an overall improvement. For in-stance, the first and second principal components describe 72.5 per cent of the variance in a transformed data exam-ple, compared with only 60.6 per cent for untransformed data. Thus the forward search is an empirical procedure, whose performance needs to be appreciated through ap-plications. The book has many of these, chosen principally from the areas of Chapters 4 to 8, and the Appendix lists in full the seventeen sets of data used. Graphical tools are widely used, resulting in three hundred and ninety figures. Each chapter is followed by extensive exercises and their solutions, and the book could be used as an advanced textbook for multivariate analysis courses. Web-sites provide the relevant software in a range of languages. This

book is full of interest for anyone undertaking multivariate analyses, clearly emphasising that uncritical use of standard methods can be misleading. University of Kent Canterbury, U.K B.J.T. Morgan

RANDOM GRAPHS FOR STATISTICAL PATTERN RECOGNITION.D.J. Marchette. Hoboken, New Jersey: Wiley, 2004, pp. xiii + 237, £47.50.

Contents:

1. Preliminaries 2. Computational geometry 3. Neighborhood graphs 4. Class cover catch diagrams 5. Cluster catch diagrams 6. Computational methods

Readership: Advanced undergraduate and graduate

students of statistical pattern recognition As far as I am aware, this is the first book to bring

together the two topics of random graphs and statistical pattern recognition. It is not about graphical models or belief networks, a familiar modern intersection of statistics and graph theory, but is about the use of the random proximity and neighborhood graphs which arise in statisti-cal pattern recognition problems. The aim of the authors is that the merger will enhance both communities. Speaking from the perspective of a researcher in pattern recognition, I think that the authors have succeeded. The ideas of random graphs in pattern recognition have always struck me as elegant, and it is nice to see them brought together in such a clear way.

The opening chapter provides background mate-rial on the requisite concepts of graph theory and statistical pattern recognition, both supervised and unsupervised. Nearest-neighbour ideas are not only an old staple of sta-tistical pattern recognition, but they also have elegant mathematicaI properties and powerful classification properties. Not surprisingly, then, they figure prominently in this book. Another attractive feature is the wide range of different pattern recognition problems and applications used to illustrate the ideas.

For anyone who wishes to gain a sound under-standing of the ideas of pattern recognition in general, as well, of course, as anyone researching in the area of random graphs applied in pattern recognition, this book would be well-worth reading. It is clearly and accessibly written, and nicely conveys the power, breadth and applicability of some very elegant ideas.

Imperial College of Science,

Technology and Medicine London, U.K. D.J. Hand

AUTOMATIC NONUNIFORM RANDOM VARlATE GENERATION.W. Hörmann, J. Leydold and G. Derflinger. Berlin: Springer-Verlag, 2004. pp. x + 441, US$69.95.

Contents: PART I: Preliminaries

1. Introduction 2. General principles in random variate generation 3. General principles for discrete distributions

PART II: Continuous Univariate Distributions 4. Transformed density rejection 5. Strip methods 6. Methods based on general inequalities 7. Numerical inversion

48

8. Comparison and general considerations 9. Distributions where the density is not known explicitly

PART III: Discrete Univariate Distributions 10. Discrete distributions

PART IV: Random Vectors 11. Multivariate distributions

PART V: Implicit Modeling 12. Combination of generation and modeling 13. Time series (Authors M. Hauser and W. Hörmann) 14. Markov chain Monte Carlo methods 15. Some simulation examples

Readership: All users of simulation, operational research

workers, statisticians

Many statistical methods make use of simulation. We now understand how to simulate standard univariate and multivariate random variables, but what do we do when we encounter a non-standard situation? Suppose for instance we want to simulate from a general stable law, specified in terms of its characteristic function, or from a random variable specified in terms of its probability generating function ― how do we proceed? What if we want to simulate from a t-distribution with parameter 2.3? What if the distribution is specified by means of its hazard function? This fascinating book is the place to look for answers to questions such as these. It brings together many of the recent developments in the area, and makes them available through the C library written by the authors, and called UNU.RAN. The authors clearly describe all the basic methods, but where the book is particularly interest-ing is when it presents a variety of "automatic" methods. For instance, the inversion method can be applied to a wide range of distributions by making use of numerical integration. Chapter 8 reviews the automatic methods that have been covered for continuous random variables, and makes recommendations so that users can decide which method is best for their particular application. Chapter 10 does the same for discrete distributions. The book ends with details of simulating time-series, MCMC methods, and applications in finance. This book is essential reading for users of simulation, and is destined to become a classical reference for the area. University of Kent, Canterbury, U.K. B.J.T. Morgan BIOSTATISTICS. A METHODOLOGY FOR THE HEALTH

SCIENCES.G. van Belle, L.D. Fisher, P.J. Heagerty and T. Lumley. Hoboken, New Jersey: Wiley, 2004, pp. xi + 871, £64.95.

Contents:

1. Introduction to biostatistics 2. Biostatistical design of medical studies 3. Descriptive statistics 4. Statistical Inference: Populations and samples 5. One- and two-sample inference 6. Counting data 7. Categorical data: Contingency tables 8. Nonparametric, distribution-free and permutation

models: Robust procedures 9. Association and prediction: Linear models with one

predictor variable 10. Analysis of variance 11. Association and prediction: Multiple regression

analysis and linear models with multiple predictor variables

12. Multiple comparisons 13. Discrimination and classification 14. Principal component analysis and factor analysis 15. Rates and proportions 16. Analysis of time to an event: Survival analysis 17. Sample size for observational studies 18. Longitudinal data analysis

19. Randomized clinical trials 20. Personal postscript

Readership: Health professionals, introductory biostatistics

students, lecturers

This new edition of a volume first published in 1993 [Short Book Reviews, Vol. 13, p. 37] is to be welcomed. The original authors have been augmented by two "experts" in "all things modern and statistical" (provide your own music). Two new chapters, entitled "Longitudinal Data Analysis" and "Randomized Clinical Trials", have been added. The latter was, surprisingly perhaps, absent from the first edition but the former clearly allows discussion of important recent developments such as generalized estimating equations, mixed models and approaches to missing data. While much of the rest of the book is little changed, this is appropriate and the presence of some marked changes indicates the thought that has been given to the new edition. The authors have also created a set of Web appendices for suitable material. Although a large volume, the first edition of this book was unusual in attempting to convey the original authors' personal pleasure in their subject. This intent is still evident. While, as for the first edition, questions might be raised about the ordering of topics and even some specific recommendations, this updated edition will help to ensure the ongoing usefulness of this valuable resource. MRC Biostatistics Unit Cambridge, U.K. V.T. Farewell

BAYESIAN APPROACHES TO CLINICAL TRIALS AND HEALTH-CARE EVALUATION.D.J. Spiegelhalter, K.R. Abrams and J.P. Myles. Chichester, U.K.: Wiley, 2004, pp. xiv + 391, £45.00.

Contents:

1. Introduction 2. Basic concepts from traditional statistical analysis 3. An overview of the Bayesian approach 4. Comparison of alternative approaches to inference 5. Prior distributions 6. Randomised controlled trials 7. Observational studies 8. Evidence synthesis 9. Cost-effectiveness, policy-making and regulation

10. Conclusions and implications for future research APPENDIX A: Websites and Software Readership: Medical statisticians, healthcare providers,

healthcare policy-makers

This important book presents the case for the use of Bayesian statistical methods in medical and clinical applications. It takes many familiar areas of clinical assessment (experimental and observational studies, sequential trials) and argues for the use of the probabilisti-cally coherent Bayesian approach in the assessment of ef-ficacy, preference and evidence. It contains interesting dis-cussions on an "integrated approach" to health care provision, and persuasively argues that the Bayesian framework is the natural one within which policy decisions and regulations should be made. The technical material is presented in an accessible style, and the examples given clearly illustrate the principles under discussion. I think this book is an essential read for those interested in an evidence-based approach to medicine, and for decision-makers in healthcare. Imperial College of Science,

Technology and Medicine London, U.K. D.A. Stephens

49

DISEASE MAPPING WITH WinBUGS AND MLwiN.A.B. Lawson, W.J. Browne, and C.L. Vidal Rodeiro. Chichester, U.K.: Wiley, 2003, pp. xiii + 277, £45.00.

Contents:

1. Disease mapping basics 2. Bayesian hierarchical modelling 3. Multilevel modelling 4. WinBUGS basics 5. MLwiN basics 6. Relative risk estimation 7. Focused clustering: The analysis of putative health

hazards 8. Ecological analysis 9. Spatially-correlated survival models

10. Epilogue APPENDIX 1: WinBUGS code for focused clustering

models APPENDIX 2: S-Plus functions for conversion of

GeoBUGS format Readership: Researchers in disease mapping

epidemiology, graduate students in statistics

This useful book outlines the models used in

statistical disease mapping, and gives details of how the models can be implemented using two packages: WinBUGS and MLwiN. Bayesian analysis is the main focus, but some pure likelihood methods are also discussed. The book makes four contributions: it provides an introduction to the models used, discusses basic Markov chain Monte Carlo (MCMC) procedures, introduces the necessary software, and illustrates the use of the software on familiar examples. I think the most important contribution is the last; it is vitally important, if Bayesian methods are to be used routinely by health scientists, that the methods are seen to be routinely implementable on widely available platforms. MCMC methods are often viewed by non-statisticians as being rather difficult to formulate and time consuming to implement. This book addresses and redresses that impression in the field of spatial epidemiology. Imperial College of Science,

Technology and Medicine London, U.K. D.A. Stephens

THE STATISTICAL EVALUATION OF MEDICAL TESTS FOR CLASSIFICATION AND PREDICTION.M.S. Pepe. Oxford University Press, 2003, pp. xvi + 302, £39.50.

Contents:

1. Introduction 2. Measures of accuracy for binary tests 3. Comparing binary tests and regression analysis 4. The receiver operating characteristic curve 5. Estimating the ROC curve 6. Covariate effects on continuous and ordinal tests 7. Incomplete data and imperfect reference tests 8. Study design and hypothesis testing 9. More topics and conclusions

Readership: Medical statisticians

Most medical statisticians will see data that relate to a diagnostic test at some time in their career. Concepts such as sensitivity, specificity and predictive values are well recognized by many but there is often less under-standing of how methodology used in this area relates to more general developments in statistical research. Also the literature on diagnostic tests has primarily been in subject- matter journals with little emphasis being given to inferen-tial details. This book now provides a welcome overview of

diagnostic testing and indeed, as reflected in the title, of classification and prediction issues more generally.

Beginning with the simplest concepts and binary tests, the book goes on to outline methods for more com-plicated situations. Particular attention is given to covariate effects and the comparison of tests. Later chapters deal with imperfect data sources, study design and an overview of additional topics, some of which may motivate future re-search efforts. It is a well-written book and provides both a clear description of methods and a serious discussion of their statistical properties. Each chapter ends with some overview remarks and exercises. The preface indicates that the book is aimed at 'the practicing statistician' but with some sections directed to the 'academic research biosta-tistician'. I believe both, and particularly those who wear two hats, will find the book of considerable value. MRC Biostatistics Unit Cambridge, U.K. V.T. Farewell

STATISTICAL ESTIMATION OF EPIDEMIOLOGICAL RISK.K.-J. Lui. Chichester, U.K.: Wiley, 2004, pp. xv + 193, £155.00.

Contents:

1. Population proportion of prevalence 2. Risk difference 3. Relative difference 4. Relative risk 5. Odds ratio 6. Generalized odds ratio 7. Attributable risk 8. Number needed to treat

APPENDIX: Maximum likelihood estimator and large-

sample theory Readership: Biostatisticians

This volume covers the main measures of risk

used by epidemiologists and clinical trialists. Each is dealt with systematically, in similarly structured chapters which describe and compare the appropriate point and interval estimators to be used under alternative sampling designs. The content is very detailed, supported by extensive and up-to-date references, many from the author himself who is undoubtedly an expert in the field. The style is extremely technical, making this textbook a very useful reference for biostatisticians working in epidemiology or clinical trials but not, in my view, an accessible source for applied research-ers.

The chapters are independent and thus each is itself a separate reference source. Every chapter begins with a brief and clear introduction to the measure being covered, namely risk (or prevalence), risk difference, relative risk (i.e. risk ratio for prevalent data and rate ratio for incidence data), and relative difference (i.e. relative risk reduction), odds ratio, generalized odds ratio, attributable risk and numbers needed to treat (i.e. the reciprocal of the risk difference). The introduction is followed by the point estimators and exact and asymptotic interval estimators appropriate for different designs. These include inverse sampling which is shown to be very useful when standard binomial sampling would lead to biased estimates. In all chapters the designs discussed include those obtained after stratification by potential confounders, clustering and paired-sampling. Several examples of real data are used to compare and discuss the different estimators. Specific references support every result and several exercises are given at the end of each chapter. Thus a very broad over-view of the most commonly used measures of risk and of the many available interval estimators is given by the au-thor. I was surprised, however, not to find a more promi-nent theoretical discussion of how the different asymptotic

50

interval estimators relate to each other through their vari-ous approximations to the likelihood function: the appendix indirectly covers this but only from a technical point of view.

At first sight the amount of details and references may appear overwhelming. However, these are systemati-cally organized so that, despite this being a very technicaI book, it is an excellent reference. More importantly, this book is likely to have an impact for further studies because of its demonstration of the advantages of inverse sampling designs when events are rare and resources limited. London School of Hygiene and Tropical Medicine London, U.K. B.L. De Stavola

DIAGNOSTIC CHECKS IN TIME SERIES.W.K. Li. Boca Raton, Florida: Chapman and Hall/ CRC Press, 2004, pp. xiii + 196, US$69.95/£42.99.

Contents:

1. Introduction 2. Diagnostic checks for univariate linear models 3. The multivariate linear case 4. Robust modeling and diagnostic checking 5. Nonlinear models 6. Conditional heteroscedasticity models 7. Fractionally differenced process 8. Miscellaneous models and topics

Readership: Statisticians, econometricians, time series

analysts

There have been several excellent monographs on the diagnostics of linear models, but this is the first and possibly definitive one for stationary time series modeling. It is of great value in bringing together the diverse literature on the topic, over three hundred references are given, and integrating them into a coherent whole. Although not over-faced with formulae, and predominantly informative discus-sion and many illustrations, main results are stated clearly as lemmas and theorems. I hope this will not put off ap-plied workers to whom this work is properly directed. The main theme of the monograph is the development and ap-plication of the generic autocorrelation-based portmanteau goodness-of-fit test to many different models, this being seen as the 'chi-square test' of time series. Whatever type of time series model you are fitting, linear or nonlinear, volatile or not, turn to this monograph for help in testing its goodness-of-fit. University of Warwick Coventry, U.K. A.J. Lawrance

STATISTICS AND FINANCE, AN INTRODUCTION.D. Ruppert. New York: Springer-Verlag, 2004, pp. xxi + 473, US$79.95.

Contents:

1. Introduction 2. Probability and statistical models 3. Returns 4. Time series models 5. Portfolio theory 6. Regression 7. The capital asset pricing model 8. Option pricing 9. Fixed income securities

10. Resampling 11. Value-at-risk 12. GARCH-models 13. Nonparametric regression and splines 14. Behavioural finance

Readership: Undergraduate or master students in engineering, mathematics, statistics and economics

The inherent interaction of statistical and financial

modelling makes this book a very useful and motivating in-strument with which to introduce students from engineer-ing, mathematics, statistics and economics to study statis-tics and/or finance. Despite being written in a very accessible style which avoids too technical details, the manuscript succeeds in covering relatively recent topics from statistics and finance, like the bootstrap, penalized splines, some VaR estimation models and behavioural finance. Several financial applications of the introduced statistical methods are presented, including for instance the fitting of volatility smiles with polynomial regression, the estimation of a continuous forward curve, the incorporation of estimation risk in portfolio choice with bootstrap methods and the estimation of a tail index in the context of risk management. Students having gained confidence with the material of this book can also be expected to be ready for advanced topics not covered in the manuscript, like for instance generalized method of moments statistics or indirect inference methods.

University of St. Gallen St. Gallen, Switzerland F. Trojani

AN INTRODUCTON TO FINANCIAL OPTION VALUATION.D.J. Higham. Cambridge University Press, 2004, pp. xxi + 273, £50.00/US$85.00 Cloth; £24.99/US$42.00 Paper.

Contents:

1. Options 2. Option valuation preliminaries 3. Random variables 4. Computer simulation 5. Asset price movement 6. Asset price model: Part I 7. Asset price model: Part II 8. Black-Scholes PDE and formulas 9. More on hedging

10. The Greeks 11. More on the Black-Scholes formulas 12. Risk neutrality 13. Solving a nonlinear equation 14. Implied volatility 15. Monte Carlo method 16. Binomial method 17. Cash-or-nothing options 18. American options 19. Exotic options 20. Historical volatility 21. Monte Carlo Part II: Variance reduction by antithetic

variates 22. Monte Carlo Part III: Variance reduction by control

variates 23. Finite difference methods 24. Finite difference methods for the Black-Scholes PDE

Readership: Undergraduate students in mathematics,

statistics and related areas

This is an introductory level text, to the extent that the author claims that no background in probability, statistics, or numerical analysis is needed, though it does require 'a working knowledge of first year calculus'. It is pitched at the same sort of level as the classic text by Wilmott, Howison, and Dewynne (The Mathematics of Financial Derivatives, CUP, 1995), though it is narrower in scope, with less emphasis on PDEs and more on stochas-tic modelling and simulation. The author summarizes the key features of the book as being: (i) detailed derivation

51

and discussion of the basic log-normal asset price model; (ii) roughly equal weight given to binomial, finite difference and Monte Carlo methods; (iii) heavy use of computational examples and figures; (iv) stand alone MATLAB code im-plementations of the main algorithms. It gives equal weight to applied mathematics, stochastics, and computational algorithms, and is structured so that each chapter could be taught in one hour, making it convenient for teaching. It would be worth considering as a text for students new to the area, but who were not intending to specialize in the topic. It could serve as a good motivating medium through which to introduce the various statistical and mathematical tools which it uses. Imperial College of Science,

Technology and Medicine London, U.K. D.J. Hand

RISK AND FINANCIAL MANAGEMENT. MATHEMATICAL AND COMPUTATIONAL METHODS.C.S. Tapiero. Chichester, U.K.: Wiley, 2004, pp. xv + 341, £55.00.

Contents: PART I: Finance and Risk Management

1. Potpourri 2. Making economic decisions under uncertainty 3. Expected utility 4. Probability finance 5. Derivatives finance

PART II: Mathematical and Computational Finance 6. Options and derivatives finance mathematics 7. Options and practice 8. Fixed income, bonds and interest rates 9. Incomplete markets and stochastic volatility

10. Value at risk and risk management Readership: Students and practitioners

interested in finance, economics, risk management

The author claims that this is not just another

book on mathematical finance. It indeed contains several discussions on economic issues which a more mathemati-cally oriented text would typically not include. The style is rather informal, however, for the more technical bits, the reader will have to sharpen his mathematical pencil some-what. It is not clear to me how the straddle between the more and less formal discussions will please the intended readership; time will tell. Towards the end, I got the feeling that the author was trying hard to put all relevant risk man-agement issues on the table; needless to say that for sev-eral concepts, this could only be achieved at the cost of lack of depth. All in all, this book gives a refreshing approach. ETH-Zürich, Zürich, Switzerland P.A.L. Embrechts

FINANCIAL MODELLING WITH JUMP PROCESSES.R. Cont and P. Tankov. Boca Raton, Florida: Chapman and Hall/CRC Press, 2004, pp. xvi + 535, US$79.95/£48.99.

Contents:

1. Financial modelling beyond Brownian motion 2. Basic tools 3. Lévy processes: Definitions and properties 4. Building Lévy processes 5. Multidimensional models with jumps 6. Simulating Lévy processes 7. Modelling financial time series with Lévy processes 8. Stochastic calculus for jump processes 9. Measure transformations for Lévy processes

10. Pricing and hedging in incomplete markets 11. Risk-neutral modelling with exponential Lévy

processes 12. Integro-differential equation and numericaI methods 13. Inverse problems and model calibration 14. Time inhomogenous jump processes 15. Stochastic volatility models with jumps

Readership: Graduate students and researchers in

financial mathematics as well as mathematicians working in banks and financial institutions

This book is an extremely rich source of

information for recent developments in the use of jump processes in financial modelling, in particular the use of Lévy processes. The contents list speaks for itself in this respect. The book as a whole is non-assuming in the sense that the mathematical and financial background the reader would seem to need is little more than what one would expect from a masters level education from any good European mathematics department offering courses in financial stochastics. The authors work at a comfortable mathematical pace choosing carefully which proofs to include and exclude and never losing sight of financial interpretation and application. The book comes with many additional perks. For example, many examples and local summaries, a balanced perspective on the shortfalls of the theory being presented, making the effort to show how standard results and expressions for semi-martingales look like for Lévy processes and clear referencing for further reading. The book is also spiced with some very interesting historical notes about prominent (French) mathematicians whose work has ultimately contributed to the foundations of financial stochastics.

The authors conclude the main body of their text by saying: "We hope that the present volume will encour-age more researchers and practitioners to contribute to this topic and improve on our understanding of theoretical, nu-merical and practical issues related to financial modelling with jump processes". I am quite convinced that this goal will be achieved. University of Utrecht Utrecht, The Netherlands A.E. Kyprianou

NOTESFERMI REMEMBERED.

J.W. Cronin (Ed.). University of Chicago Press, 2004, pp. xi + 287, US$45.00.

From the paper cover: "Nobel laureate and

scientific luminary Enrico Fermi (1901-1954) was a pioneering nuclear physicist whose contributions to the field were numerous, profound, and lasting. Best known for

his involvement with the Manhattan Project and his work at Los Alamos that led to the first self-sustained nuclear reaction and ultimately to the production of electric power and plutonium for atomic weapons, Fermi and his legacy continue to color the character of the sciences at the University of Chicago. During his tenure as professor of physics at the Institute for Nuclear Studies, Fermi attracted an extraordinary scientific faculty and many talented students – ten Nobel Prizes were awarded to faculty or students under Fermi's tutelage."

52

HANDBOOK OF MATHEMATICS, 4th edition. I.N. Bronshtein, K.A. Semendyayev, G. Musiol and H. Muehlig. Berlin: Springer-Verlag, 2004, pp. xiii + 1153, US$59.95.

From the back cover: "This guide book to

mathematics contains in handbook form the fundamental working knowledge of mathematics which is needed as an everyday guide for working scientists and engineers, as well as for students. Easy to understand, and convenient to use, this guide book gives concisely the information necessary to evaluate most problems which occur in concrete applications. For the 4th edition, the concept of the book has been completely re-arranged. The new emphasis is on those fields of mathematics that became more important for the formulation and modelling of technical and natural processes, namely Numerical Mathematics, Probability Theory and Statistics, as well as Information Processing."

HANDBOOK OF BETA DISTRIBUTION AND ITS APPLICATIONS.A.K. Gupta and S. Nadarajah (Eds.). New York: Dekker, 2004, pp. viii + 571, US$165.00/£95.00.

From the back cover: "A milestone in the pub-

lished literature on the subject, this first-ever Handbook of Beta Distribution and Its Applications clearly enumerates the properties of beta distributions and related mathemati-cal notions, summarizes modern applications in a variety of fields, and reviews up-and-coming progress from the front-lines of statistical research and practice.

"Demonstrates the applicability of beta distribu-tions in such fields as economics, quality control, soil sci-ence, and biomedicine.

"Tapping the acumen of 25 distinguished con-tributors, the Handbook considers the centrality of beta distributions in Bayesian inference … applications for beta distributions in stochastic processes … the beta-binomial model and applications of the beta-binomial distribution … the utility of beta distributions in bioassay … applications of Dirichlet integrals … and surveys generalizations of the beta distribution … approximations and tables of beta dis-tributions … distributions with beta conditionals … and lim-ited-range distributions with informative dropout."

HANDBOOK OF SCHEDULING. Algorithms, Models, and Performance Analysis. J.Y-T. Leung (Ed.). Boca Raton, Florida: Chapman and Hall/CRC Press, 2004, pp. xix + 1159, US$139.95/£85.00.

From the back cover: "Handbook of Scheduling:

Algorithms, Models, and Performance Analysis: Provides full coverage of the most recent advances in scheduling, gathering authors and topics from across the fields of management, industrial engineering, operations research, and computer science; Includes many applications, ad-dressing scheduling problems in transportation and proc-ess industries, as well as in hospitals and educational in-stitutions; Examines job shop, flow shop, open shop, and cycle shop problems; Covers five major objective functions in classical scheduling theory: makespan, maximum late-ness, total weighted completion time, total weighted num-ber of late jobs, and total weighted tardiness; Introduces constraint programming (CP) and a new vehicle routing heuristic known as Very Large Scale Neighborhood Search; Covers extensively real-time scheduling and sto-chastic scheduling; Introduces new scheduling models that are different from the classical model."

CONSUMER PRICE INDEX MANUAL. THEORY AND PRACTICE. U.N. International Labour Office. Geneva: International Labour Office, 2004, pp. xxxi + 535, CHF200.

From the back cover: "The consumer price index

(CPI) measures the rate at which the prices of consumer goods and services are changing over time. It is a key statistic for purposes of economic and social policy making, especially monetary policy and social policy, and has substantial and wide-ranging implications for governments, business and workers, as well as households.

"This important and comprehensive manual pro-vides guidelines for statistical offices and other agencies responsible for constructing CPIs and explains in depth the methods that are used to calculate a CPI. it also examines the underlying economic and statistical concepts and prin-ciples needed for making choices in efficient and cost-ef-fective ways and for appreciating the full implications of those choices.

"The following international organizations, con-cerned both with the measurement of inflation and with policies designed to control it, have collaborated on the preparation of this manual: the International Labour Office; the International Monetary Fund; the Organisation for Eco-nomic Co-operation and Development; the Statistical Office of the European Communities (EUROSTAT); the United Nations Economic Commission for Europe; and the World Bank." METHODS FOR TESTING AND EVALUATING SURVEY

QUESTIONNAIRES.S. Presser, J.M. Rothgeb, M.P. Comper, J.T. Lessler, E. Martin, J. Martin and E. Singer. Hoboken, New Jersey: Wiley, 2004, pp. xvi + 606, £29.50.

From the book cover: "Over the past two

decades, methods for the development, evaluation, and testing of survey questionnaires have undergone radical change. Research has now begun to identify the strengths and weaknesses of various testing and evaluation methods, as well as to estimate the methods' reliability and validity. Expanding and adding to the research presented at the International Conference on Questionnaire Development, Evaluation and Testing Methods, this title presents the most up-to-date knowledge in this burgeoning field.

"The only book dedicated to the evaluation and testing of survey questionnaires, this practical reference work brings together the expertise of over fifty leading, international researchers from a broad range of fields. The volume is divided into seven sections: cognitive interviews, mode of administration, supplements to conventional pretests, special populations, experiments, multi-method applications, and statistical modeling." THE DUTCH VIRTUAL CENSUS OF 2001: ANALYSIS

AND METHODOLOGY.E.S. Nordholt, M. Hartgers and R. Gircour (Eds.). Voorburg, The Netherlands: Statistics Netherlands, 2004, pp. 276.

From the back cover: "Data from many different

sources were combined to produce the Dutch Census Tables of 2001. Since the last census based on a complete enumeration was held in 1971, the willingness of the population to participate has fallen sharply. Statistics Netherlands found an alternative in the Virtual Census, using available registers and surveys. The Virtual Census is cheaper, comparable to earlier Dutch censuses, and more socially acceptable. The Netherlands takes up a unique position in the European Census Round. The table results are not only comparable with the earlier Dutch

53

censuses but also with those of the other countries in the 2001 Census Round.

"The part on analysis in this book deals with the following topics: key figures, population by household characteristics, working people, young people, seniors, foreign people, and commuting. A historical comparison with earlier Dutch censuses is made and regional distributions are discussed with special attention to ten major cities in the Netherlands. Finally, the results of the 2001 Census in the Netherlands are compared with the results in other European countries.

"The part on methodology deals with the input, throughput and output phases placing special emphasis on how the new methodology of repeated weighting was applied in producing the set of census tables."

FOREST PRODUCTS: STATISTICAL INFORMATION SYSTEMS OF EU AND EFTA.P. Wardle, J. van Brusselen, B. Micke and A. Sohnet. Leiden: Brill, 2003, pp. xvii + 163, €63/US$78.99.

From the book description: "This book is the only

one of its kind to review the commodity coding, definitions and methodology applying to the collection of forest products production and trade statistics. The analysis ―both qualitative as quantitative ― contains valuable information for anybody who wants to gain more insight in the methodology behind the figures. Recommendations are made for improving the data collection framework."

PROBABILITY, FINANCE AND INSURANCE: PROCEEDINGS OF A WORKSHOP AT THE UNIVERSITY OF HONG KONG.T.L. Lai, H. Yang and S.P. Yung (Eds.). Singapore: World Scientific, 2004, pp. ix + 242, £44.00.

From the back cover: "This workshop was the first

its kind in bringing together researchers in probability theory, stochastic processes, insurance and finance from mainland China, Taiwan, Hong Kong, Singapore, Australia and the United States. In particular, as China has joined the WTO, there is a growing demand for expertise in actuarial sciences and quantitative finance. The strong probabillity research and graduate education programs in many of China's universities can be enriched by their outreach in fields that are of growing importance to the country's expanding economy, and the workshop and its proceedings can be regarded as the first step in this direc-tion.

"This book presents the most recent develop-ments in probability, finance and actuarial sciences, espe-cially in Chinese probability research. It focusses on the integration of probability theory with applications in finance and insurance. It also brings together academic research-ers and those in industry and government. With contribu-tions by leading authorities on probability theory ― par-ticularly limit theory and large derivations, valuation of credit derivatives, portfolio selection, dynamic protection and ruin theory ― it is an essential source of ideas and in-formation for graduate students and researchers in prob-ability theory, mathematical finance and actuarial sciences, and thus every university should acquire a copy."

THE THEORY OF INFORMATION AND CODING: STUDENT EDITION.R. McEliece. Cambridge University Press, 2004, pp. xii + 397, £35.00/US$60.00.

From the back cover: "This is a revised edition of

McEliece's classic, published with students in mind. It is a self-contained introduction to all basic results in the theory of information and coding. This theory was developed to

deal with the fundamental problem of communication, that of reproducing at one point, either exactly or approxi-mately, a message selected at another point. There is a short and elementary overview introducing the reader to the concept of coding. Then, following the main results, the channel and source coding theorems, there is a study of specific coding schemes which can be used for channel and source coding. This volume can be used either for self-study, or for a graduate/undergraduate-level course at uni-versity. It includes dozens of worked examples and several hundred problems for solution. The exposition will be easily comprehensible to readers with some prior knowledge of probability and linear algebra."

THE PARADOX OF CHOICE.B. Schwartz. New York: ICCO (Harper Collins), 2004, pp. xi + 265, US$23.95.

From the book jacket: "In The Paradox of Choice,

Barry Schwartz explains at what point choice ― the hallmark of individual freedom and self-determination that we so cherish ― becomes detrimental to our psychological and emotional well-being. In accessible, engaging, and anecdotal prose, Schwartz shows how the dramatic explosion in choice ― from the mundane to the profound challenges of balancing career, family, and individual needs ― has paradoxically become a problem instead of a solution. Schwartz also shows how our obsession with choice encourages us to seek that which makes us feel worse.

"By synthesizing current research in the social sciences, Schwartz makes the counterintuitive case that eliminating choices can greatly reduce the stress, anxiety, and busyness of our lives. He offers eleven practical steps on how to limit choices to a manageable number, have the discipline to focus on those that are important and ignore the rest, and ultimately derive greater satisfaction from the choices you have to make." THE SKEPTIC'S DICTIONARY: A COLLECTION OF

STRANGE BELIEFS, AMUSING DECEPTIONS AND DANGEROUS DELUSIONS.R.T. Carroll. Hoboken, New Jersey: Wiley, 2003, pp. xi + 446, £13.95.

From the back cover: "Featuring close to 400

definitions, arguments, and essays on topics ranging from acupuncture to zombies, The Skeptic's Dictionary is a lively, commonsense trove of detailed information on all things supernatural, occult, paranormal, and pseudoscien-tific. It covers such categories as alternative medicine; cryptozoology; extraterrestrials and UFOs; frauds and hoaxes; junk science; logic and perception; New Age en-ergy; and the psychic. For the open-minded seeker, the soft or hardened skeptic, and the believing doubter, this book offers a remarkable range of information that puts to the test the best arguments of true believers." WORLD CATALOGUE OF MAXIMUM OBSERVED

FLOODS/RÉPERTOIRE MONDIAL DES CRUES MAXIMALES OBSERVÉES.Compiled by R. Herschy. Wallingford, U.K.: IAHS Press, 2003, pp. xxxiv + 285, £80.00.

This is a new edition of the 1989 Catalogue

(prepared by J.A. Lodier and M. Roche) with revisions and updates.

Data on floods are listed for one hundred and twenty countries, including newly provided data for 48 countries. The data for each country includes the location of observation sites and background information about the drainage basins, the maximum instantaneous discharge observed.

54

TOWARDS COHERENCE BETWEEN CLASSROOM ASSESSMENT AND ACCOUNTABILITY.M. Wilson (Ed.). Chicago, Illinois: National Society for the Study of Education, 2004, pp. xii + 290, US$39.00/£27.50.

From the book jacket: "There has been insuffi-

cient attention paid to the central place of the classroom in

thinking about the role of assessment in educational ac-countability. Towards Coherence Between Classroom As-sessment and Accountability contributes to the discourse among educational policymakers, professionals, and re-searchers in this important area by encouraging reflection and scholarly exchange on the topic, and is designed with a structure meant to promote discussion and debate."

NEW EDITIONS ANALYSING SURVIVAL DATA FROM CLINICAL TRIALS

AND OBSERVATIONAL STUDIES. E. Marubini and M.G. Valsecchi. Chichester, U.K.: Wiley, 2004, pp. xvi + 414, £34.95. [Original 1995, Short Book Reviews, Vol. 15, p. 23]

COMBINATORICS, 2nd edition.

R. Morris. Hoboken, New Jersey: Wiley, 2003, pp. xi + 556, £58.95.

DATA ANALYSIS FOR MANAGERS WITH MICROSOFT® EXCEL, 2nd edition. S.C. Albright, W.L. Winston and C. Zappe. Australia: Thomson Brooks/Cole, 2004, pp. xxi + 952 + CD.

DATA ANALYSIS USING MICROSOFT® EXCEL. Updated

for Office XP, 3rd edition. M.R. Middleton. Australia: Thomson Brooks/Cole, 2004, pp. xv + 280.

ELEMENTARY STATISTICS, 9th edition. R. Johnson and P. Kuby. Australia: Thomson Brooks/Cole, 2004, pp. xvi + 782 + CD.

INITIAL-BOUNDARY VALUE PROBLEMS AND THE NAVIER-STOKES EQUATIONS. H.-O. Kreiss and J. Lorenz. Philadelphia: Society for Industrial and Applied Mathematics, 2004, pp. xvii + 402, US$48.00. [Original 1984]

INTRODUCTION TO PROBABILITY MODELS. Operations Research: Volume Two, 4th edition. W.L. Winston. Australia: Thomson Brooks/Cole, 2004, pp. xiii + 729 + CD.

INTRODUCTORY STATISTICS, 5th edition. P.S. Mann. Hoboken, New Jersey: Wiley, 2004, pp. xiv + 110, £34.95.

KENDALL'S ADVANCED THEORY OF STATISTICS, 6th edition. Vol 2a: Classical Inference and the Linear Model. A. Stuart, K. Ord and S. Arnold. London: Arnold, 2004, pp. xxii + 885, £85.00. [First Published, 1999; Short Book Reviews,

Vol. 19, p. 41]

MATHEMATICAL NAVIGATOR: MATHEMATICS, STATISTICS AND GRAPHICS, 2nd edition. H. Ruskeepää. Burlington, Massachusetts: Elsevier, 2004, pp. xx + 844.

MIND ON STATISTICS, 2nd edition. J.M. Utts and R.F. Heckard. Australia: Thomson Brooks/Cole, 2004, xxi + 646 + CD. [Original 2001, Short Book Reviews, Vol. 21, p. 57]

MULTIVARIATE STATISTICAL METHODS. A Primer. B.F.J. Manly. Boca Raton, Florida: Chapman and Hall/CRC Press, 2005, pp. 214, US$49.95/£29.99. [Original 1986, Short Book Reviews, Vol. 7, p. 25]

OPERATIONS RESEARCH. Applications and Algorithms, 4th edition. W.L. Winston. With cases by J.B. Goldberg. Australia: Thomson Brooks/Cole, 2004, pp. xvi + 1418 + CD.

PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 6th edition. J.L. Devore. Australia: Thomson Brooks/Cole, 2004, pp. xvi + 795 + CD.

SCIENCE FROM FISHER INFORMATION: A UNIFICATION. B.R. Frieden. Cambridge University Press, 2004, pp. xi + 490, £80.00/US$110.00 Cloth; £40.00/US$65.00 Paper. [Revised version of Physics from Fisher Information: A Unification, 1998; Short Book Reviews, Vol. 20, p. 22]

STATISTICS FOR MANAGAMENT AND ECONOMICS, 6th edition. G. Keller and B. Warrack. Australia: Thomson Brooks/Cole, 2004, pp. xxii + 690 + CD.

THE SKEPTICAL ENVIRONMENTALIST: MEASURING THE REAL STATE OF THE WORLD. B. Lomborg. Cambridge University Press, 2004, pp. xxiii + 515. [Original 2002, Short Book Reviews, Vol. 22, p. 15]

UNITED NATIONS STATISTICAL OFFICE PUBLICATIONS RECENTLY ISSUED

2000 ENERGY BALANCES AND ELECTRICITY PROFILES. ST/ESA/STAT/SER.W/II. 2004, U.N. Sales No. E/F.04.xvii.2, pp. xxxiii + 472.

2001 ENERGY STATISTICS YEARBOOK. ST/ESA/STAT/SER. J/45, 2004, U.N. Sales No. E/F.04.xvii.6, pp. viii + 510.

HANDBOOK ON THE COLLECTION OF FERTILITY AND MORTALITY DATA. Studies in Methods Series F., No. 92 ST/ESA/STAT/SER. F/92, 2004, U.N. Sales No. E.03.xvii.11, pp. vii + 129.

INDICATORS FOR MONITORING THE MILLENIUM DEVELOPMENT GOALS ST/ESA/STAT/SER.F.95 U.N. Sales No. E.03.xvii.18. 2004, pp. viii + 106.

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INTERNATIONAL STANDARD INDUSTRIAL CLASSIFICATION OF ALL ECONOMIC ACTIVITIES (ISIC) REVISION 3.1 Series M. No 4. Rev 3.1 ST/ESA/STAT/SER.M/4/Rev 3.1, 2004, U.N. Sales No. E.03.xvii.4, pp. 251.

NATIONAL ACCOUNTS: A PRACTICAL INTRODUCTION

STUDIES IN METHODS. SERIES F. NO 85. Handbook of National Accounting. ST/ESA/STAT/SER.F/85. U.N. Sales No. E.04.xvii.4. 2004, pp. vii + 134.

POPULATION AND VITAL STATISTICS REPORT. Statistical Papers, Series A. Vol. LV, Nos 3 and 4. Data Available as of 31 December 2003. ST/ESA/STAT/SER A/226/227, 2004, pp. 19.

UPDATES AND AMENDMENTS TO THE SYSTEM OF NATIONAL ACCOUNTS 1993. ST/ESA/STAT/SER. F/2/Rev.4/Add 2004, U.N. Sales No. E.04.xvii.8, pp. viii + 133

COLLECTED PAPERS, TABLES, EDITED VOLUMES AND PROCEEDINGS APPLIED SEQUENTIAL METHODOLOGIES. Real-World

Examples With Data Analysis. N. Mukhopadhyay, S. Datta and S. Chattopadhyay (Eds.). New York: Dekker, 2004, pp. xxiv + 461, US$150.00/£94.00.

CALIBRATION AND RELIABILITY IN GROUND WATER MODELLING: A Few Steps Closer to Reality. K. Kovar and Z. Hrkal (Eds.). Wallingford, U.K.: IAHS Press, 2003, pp. x + 525, £78.80.

EROSION PREDICTION IN UNGAUGED BASINS: Integrating Methods and Techniques. D.H. de Boer, W. Froehlich, T. Mizuyama and A. Pietroniro (Eds.). Wallingford, U.K.: IAHS Press, 2003, pp. xi + 250.

EXPLANATORY ITEM RESPONSE MODELS. A Generalized Linear and Nonlinear Approach. P. De Boeck and M. Wilson (Eds.). New York: Springer-Verlag, 2004, pp. xxii + 382, US$69.95.

GRAPHICS INTERFACE 2004. 17-19 May 2004, London, Ontario. Canadian Human-Computer Communications Society. W. Heidrich and R. Balakrishnan (Eds.). Natick, Massachusetts: A.K. Peters. 2004, pp. v + 279, US$70.00.

HANDBOOK OF COMPUTATIONAL AND NUMERICAL METHODS IN FINANCE. S.T. Rachev (Ed.). Boston: Birkhäuser, 2004, pp. vi + 435, US$79.95.

INSIGHT INTO IMAGES. Principles and Practice for Segmentation, Registration, and Image Analysis. T.S. Yoo (Ed.). Wellesley, Massachusetts: A.K. Peters, 2004, pp. xv + 393, US$64.00.

LOGIC COLLOQUIUM '99. Proceedings of the Annual Summer Meeting of the Association for Symbolic Logic, held in Utrecht, Netherlands, August 1-6, 1999. J. van Eijck, V. van Oostrom and A. Visser (Eds.). Natick, Massachusetts: Association For Symbolic Logic, 2004, pp. viii + 208, US$70.00, Cloth; US$40.00, Paper.

MATHEMATICAL ADVENTURES FOR STUDENTS AND AMATEURS. D.F. Hayes and T. Shubin (Eds.). Washington, D.C.: The Mathematical Association of America, 2004, pp. xi + 291, US$37.50.

MATHEMATICS AND COMPUTER SCIENCE III. Algorithms, Trees, Combinatorics and Probabilities. M. Drmota, P. Flajolet, D. Gardy and B. Gittenberger (Eds.). Basel: Birkhäuser, 2004, pp. xv + 554, CHF178.00; €108.00.

PARAMETRIC AND SEMIPARAMETRIC MODELS WITH APPLICATIONS TO RELIABILITY, SURVIVAL ANALYSlS, AND QUALITY OF LIFE. M.S. Nikulin, N. Balakrishnan, M. Mesbah and N. Limnios. (Eds.). Boston: Birkhäuser, 2004, pp. xii + 555, US$115.00.

PROBABILITY, FINANCE AND INSURANCE: Proceedings of a Workshop at the University of Hong Kong. T.L. Lai, H. Yang and S.P. Yung (Eds.). Singapore: World Scientific, 2004, pp. ix + 242, £44.00.

SEDIMENT TRANSFER THROUGH THE FLUVIAL SYSTEM. V. Golosov, V. Belyaev and D.E. Walling (Eds.). Wallingford, U.K.: IAHS Press, 2004, pp. x + 498.

THE BASIS OF CIVILIZATION – WATER SCIENCE? S.C. Rodde and L. Ubertini (Eds.). Wallingford, U.K.: IAHS Press, 2004, pp. ix + 334.

THE SHARPEST CUT. The Impact of Manfred Padberg and His Work. M. Grotschel (Ed.). Philadelphia: Society for Industrial and Applied Mathematics, 2004, pp. xi + 380, US$99.00.

USA AND INTERNATIONAL MATHEMATICAL OLYMPIADS 2003. T. Andreescu and Z. Feng (Eds.). Washington, D.C.: The Mathematical Association of America, 2004, pp. xvi + 85, US$26.95.

WASTEWATER RE-USE AND GROUNDWATER QUALITY. J. Steenvoorden and T. Endreny (Eds.). Wallingford, U.K.: IAHS Press, 2004, pp. vii + 111.

BOOKS RECEIVED

ARTIFICIAL INTELLIGENCE FOR COMPUTER GAMES.

An Introduction. J.D. Funge. Wellesley, Massachusetts: A.K. Peters, 2004, pp. x + 146, US$35.00.

BUSINESS ECONOMICS AND FINANCE WITH MATLAB, GIS, AND SIMULATION MODELS. P.L. Anderson.

Boca Raton, Florida: Chapman and Hall/CRC Press, 2005, pp. 472.

DATA ANALYSIS WITH MICROSOFT® EXCEL. Updated for Windows XP. K.N. Berk and P. Carey. Australia: Thomson Brooks/Cole, 2004, pp. xix + 579 + CD.

57

58

DECISION MAKING WITH INSIGHT. Includes Insight.xla 2.0. S.L. Savage. Foreword by H. Markowitz. Australia: Thomson Brooks/Cole, 2003, pp. xxii + 360 + CD.

DOING DATA ANALYSIS WITH MINITAB 14. R.H. Carver. Australia: Thomson Brooks/Cole, 2004, pp. xvii + 356 + CD.

EROSION AND SEDIMENT TRANSPORT MEASUREMENT IN RIVERS: Technological And Methodological Advances. J. Bogen, T. Fergus, and D.E. Walling. Wallingford, U.K.: IAHS Press, 2003, pp. viii + 237, £45.50.

EXCEL ESSENTIALS. Using MICROSOFT® EXCEL For Data Analysis & Decision Making. A.J.H. Taylor. Australia: Thomson Brooks/Cole, 2002, pp. 6 + CD.

FUNDAMENTALS OF OCEAN CLIMATE MODELS. S.M. Griffies. Princeton University Press, 2004, pp. xxxiv + 518, US$65.00; £41.95

INTERNET COMPANION FOR STATISTICS. Guide and Activities For The Web. M.D. Larsen. Australia: Thomson Brooks/Cole, 2004, pp. 102.

INTRODUCTION TO BAYESIAN STATISTICS. W.M. Bolstad. Hoboken, New Jersey: Wiley, 2004, pp. xviii + 354, £50.50.

ITEM RESPONSE THEORY. Parameter Estimation Techniques, 2nd edition, revised and expanded. F.B. Baker and S.-H. Kim. New York: Dekker, 2004, pp. xx + 495 + CD, US$99.95/£56.99.

JMP IN. Statistical Discovery Software. Australia: Thomson Brooks/Cole, 2004, CD, US$79.95.

KENDALL'S ADVANCED THEORY OF STATISTICS, 6th edition. Volume I. Distribution Theory. A. Stuart and K. Ord London: Arnold, 2003, pp. xx + 676, £85.00. [Original 1999, Short Book Reviews, Vol. 14, p. 42].

MARINE ACOUSTICS. Direct and Inverse Problems. J.L. Buchanan, R.P. Gilbert, A. Wirgin and Y.S. Xu. Philadelphia: Society for Industrial and Applied Mathematics, 2004, pp. xii + 336, US$80.00.

MATHEMATICAL DELIGHTS. R. Honsberger. Washington, D.C.: The Mathematical Association of America, 2004, pp. ix + 252, US$39.50.

MEDICAL STATISTICS MADE EASY. M. Harris and G. Taylor. London: Martin Dunitz Taylor & Francis Group, 2004, pp. xii + 114, US$14.95/£12.99.

MEET MINITAB. Student Release 14 for Windows. Australia: Thomson Brooks/Cole, 2005, pp. v + 105 + CD.

METAPROGRAMMING GPUs WITH SH. M. McCool and S. Du Toit. Wellesley, Massachusetts: A.K. Peters, 2004, pp. xvii + 290, US$44.00.

MORPHS, MALLARDS AND MONTAGES. Computer-Aided Imagination. A. Glassner. Wellesley, Massachusetts: A.K. Peters, 2004, pp. xiv + 328, US$49.00.

MULTIVARIATE PROBABILITY. J.H. McColl. London: Arnold, 2004, pp. x + 304, £19.99.

NUMERICAL COMPUTING WITH MATLAB. C.B. Moler. Philadelphia: Society for Industrial and Applied Mathematics, 2004, pp. xi + 336, US$42.50.

NUMERICAL ISSUES IN STATISTICAL COMPUTING FOR THE SOCIAL SCIENTIST. M. Altman, J. Gill and M.P. MacDonald. Hoboken, New Jersey: Wiley, 2004, pp. xv + 323, £52.95.

PROBABILITY MATCHING PRIORS: Higher Order Asymptotics. G.S. Datta and R. Mukerjee. New York: Springer-Verlag, 2004, pp. x + 127, US$59.95.

RANKED SET SAMPLING. Theory and Applications. Z. Chen, Z. bai and B.K. Sinha. New York: Springer-Verlag, 2004, pp. xii + 224, US$59.95.

RATS HANDBOOK FOR ECONOMETRIC TIME SERIES. W. Enders. Hoboken, New Jersey: Wiley, 1996, pp. vii + 204.

RESOURCES FOR THE STUDY OF REAL ANALYSIS. R.L. Brabenec. Washington D.C.: The Mathematical Association of America, 2004, pp. xii + 231, US$48.95.

SEEING STATISTICS. G.H. McClelland. Australia: Thomson Brooks/Cole, 2004, CD.

STATISTICS FOR THE QUALITY CONTROL CHEMISTRY LABORATORY. E. Mullins. Cambridge: Royal Society of Chemistry, 2003, pp. xviii + 456, £34.95.

THE SIAM 100-DIGIT CHALLENGE. A Study in High-Accuracy Numerical Computing. F. Bornemann, D. Laurie, S. Wagon and J. Waldvogel. With a Foreword by D.H. Bailey. Philadelphia: Society for Industrial and Applied Mathematics, 2004, pp. xi + 306, US$57.00.

59

INDEX VOLUME 24, 2004

Aitken, C.C. and Taroni, F. Statistics and the Evaluation of Evidence for Forensic Scientists, 2nd edition. (D.J. Balding) p. 43.

Albert, J. Teaching Statistics Using Baseball. (F.H. Berkshire) p. 2.

Anderson, T.W., 3rd edition. An Introduction to Multivariate Statistical Analysis. (W.J. Krzanowski) p. 3.

Atkinson, A.C., Riani, M. and Cerioli, A. Exploring Multivariate Data with the Forward Search. (B.J.T. Morgan) p. 47.

Aven, T. Foundations of Risk Analysis. A Knowledge and Decision-Oriented Perspective (P.A.L. Embrechts) p. 12.

Ayyub, B.M. Risk Analysis in Engineering and Economics. (J.L. Teugels) p. 13.

Bailey, R.A. Association Schemes. Designed Experiments, Algebra and Combinatorics. (L.V. White) p. 26.

Baldi, P., Frasconi, P. and Smyth, P. Modelling the Internet and the Web: Probabilistic Methods and Algorithms. (D.J. Hand) p. 27.

Barnett, V. Environmental Statistics Methods and Applications. (P. Prescott) p. 43.

Bartholomew, D.J. Measuring Intelligence: Facts and Fallacies. (D.J. Hand) p. 41.

Beran, J. Statistics in Musicology. (D.F. Andrews) p. 1.

Berk, R.A. Regression Analysis. (A Constructive Critique.) (N.R. Draper) p. 26.

Blischke, W.R. and Prabhakar Murthy, D.N. (Eds.). Case Studies in Reliability and Maintenance. (M.J. Crowder) p. 10.

Bluhm, C., Overbeck, L. and Wagner, C. An Introduction to Credit Risk Modeling. (G. Cesari) p. 12.

Borovkov, K. Elements of Stochastic Modelling. (J.R. Leslie) p. 23.

Borowiak, D.S. Financial and Actuarial Statistics. An Introduction. (J. Hüsler) p. 30.

Bucklew, J.A. Introduction to Rare Event Simulation. (S. Asmussen) p. 32.

Cacuci, D.G. Sensitivity and Uncertainty Analysis: Theory, Volume I. (C.A. Fung) p. 33.

Campbell, S.L. and Nikoukhah, R. Auxiliary Signal Design for Failure Detection. (G.C. Goodwin) p. 32.

Carmona, R. Statistical Analysis of Financial Data in S-Plus. (D.L. McLeish) p. 30.

Chatfield, C. The Analysis of Time Series. An Introduction, 6th edition. (J.L. Teugels) p. 10.

Collett, D. Modelling Survival Data in Medical Research, 2nd edition. (J.M. Juritz) p. 6.

Cont, R. and Tankov, P. Financial Modelling with Jump Processes. (A.E. Kyprianou) p. 51.

Cramer, J.S. Logit Models from Economics and other Fields. (C.M. O'Brien) p. 5.

D'Agostino, G. Bayesian Reasoning in Data Analysis: A Critical Introduction. (V.V. Fedorov) p. 28.

Dasu, T. and Johnson, T. Exploratory Data Mining and Data Cleaning. (D.J. Hand) p. 11.

Davison, A.C. Statistical Models. (R.E. Chandler) p. 45.

Desu, M.M. and Raghavarao, D. Nonparametric Statistical Methods for Complete and Censored Data. (N.D.C. Veraverbeke) p. 8.

Dewdney, A.K. Beyond Reason: 8 Great Problems that Reveal the Limit of Science. (F.H. Berkshire) p. 42.

Edwards, A.W.F. Cogwheels of the Mind. The Story of Venn Diagrams. (F.H. Berkshire) p. 42.

Elston, R., Olson, J. and Palmer, L. (Eds.). Biostatistical Genetics and Genetic Epidemiology. (J. Whittaker) p. 5.

Evans, M.I. and Rosenthal, J.S. Probability and Statistics. The Science of Uncertainty. (S. Starkings) p. 3.

Fan, J. and Yao, Q. Nonlinear Time Series: Nonparametric and Parametric Methods. (M.J. Crowder) p. 10.

Finkelstädt, B. and Rootzén, H. (Eds.). Extreme Values in Finance, Telecommunications, and the Environment. (D.L. McLeish) p. 30.

Gelman, A., Carlin, J.B., Stern, H.S. and Rubin, D.B. Bayesian Data Analysis, 2nd edition. (C.A. Fung) p. 9.

Gelman, A. and Meng, X.-L. Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives. (M.J. Crowder) p. 44.

Ghosh, J.K. and Ramamoorthi, R.V. Bayesian Nonparametrics. (M.J. Crowder) p. 9.

Gibbons, J.D. and Chakraborti, S. Nonparametric Statistical Inference, 4th edition. (F.R. Jolliffe) p. 8.

Giudici, P. Applied Data Mining: Statistical Methods for Business and Industry. (D.J. Hand) p. 12.

Golberg, M.A. and Cho, H.A. Introduction to Regression Analysis. (N.R. Draper) p. 46.

Gower, J.C. and Dijksterhuis, G.B. Procrustes Problems. (W.J. Krzanowski) p. 28.

Gustafson, P. Measurement Error and Misclassification in Statistics and Epidemiology. (D.J. Hand) p. 5.

Haigh, J. Taking Chances: Winning with Probability, new edition. (D.R. Bellhouse) p. 1.

Haining, R. Spatial Data Analysis: Theory and Practice. (M.J. Crowder) p. 29.

Härdle, W., Müller, M., Sperlich, S. and Werwatz, A. Nonparametric and Semiparametric Models. (T.P. Hettmansperger) p. 46.

Havil, J. Gamma. Exploring Euler's Constant. (M.R. Murty) p. 22.

Higgins, J.J. An Introduction to Modern Nonparametric Statistics. (N.R. Draper) p. 46.

Higham, D.J. An Introducton to Financial Option Valuation. (D.J. Hand) p. 50.

Hörmann, W., Leydold, J. and Derflinger, G. Automatic Nonuniform Random Varlate Generation (B.J.T. Morgan) p. 47.

Ingster, Y.I. and Suslina, I.A. Nonparametric Goodness-Of-Fit Testing under Gaussian Models. (N.D.C. Veraverbeke) p. 8.

Jaynes, E.T. Probability Theory: The Logic of Science. (D.J. Hand) p. 22.

Jewel, N.P. Statistics for Epidemiology. (T.A. Louis) p. 24.

Johnson, V.E. Grade Inflation – A Crisis in College Education. (F.H. Berkshire) p. 2.

Kleiber, C. and Kotz, S. Statistical Size Distributions in Economics and Actuarial Sciences. (C.D. Kemp) p. 30.

Knottnerus, P. Sample Survey Theory. Some Pythagorean Perspectives. (J.N.K. Rao) p. 4.

Korb, K.B. and Nicholson, A.E. Bayesian Artificial Intelligence. (B.I. Penkov) p. 27.

60

Kotz, S. and Nadarajah, S. Multivariate t-Distributions and Their Applications. (C.D. Kemp) p. 45.

Lahiri, S.N. Resampling Methods for Dependent Data. (D.J. Thomson) p. 31.

Lange, K. Applied Probability. (J.L. Teugels) p. 3. Lattin, J., Carroll, J.D. and Green, P.E. Analyzing

Multivariate Data. (S. Gardner) p. 4. Lawson, A.B., Browne, W.J. and Vidal Rodeiro, C.L.

Disease Mapping with WinBUGS and MLwiN. (D.A. Stephens) p. 49.

Le, C.T. Introductory Biostatistics. (F.R. Jolliffe) p. 4. Lee, E.T. and Wang, J.W. Statistical Methods for

Survival Data Analysis, 3rd edition. (B. De Stavola) p. 7.

Lee, J. A First Course in Combinatorial Optimization. (S. Powell) p. 42.

Lejeune, M. Statistique. La Théorie et Ses Applications. (N.D.C. Veraverbeke) p. 42.

Li, W.K. Diagnostic Checks in Time Series. (A.J. Lawrance) p. 50.

Lindsey, J.K. Introduction to Applied Statistics: A Modelling Approach, 2nd edition. (D.J. Hand) p. 23.

Lui, K-J. Statistical Estimation of Epidemiological Risk. (B.L. De Stavola) p. 49.

Marchette, D.J. Random Graphs for Statistical Pattern Recognition. (D.J. Hand) p. 47.

Melnikov, A. Risk Analysis in Finance and Insurance. (P.A.L. Embrechts) p. 13.

Mitra, S. and Acharya, T. Data Mining: Multimedia, Soft Computing, and Bioinformatics. (D.J. Hand) p. 28.

Møeller, J. and Waagepetersen, R.P. Statistical Inference and Simulation for Spatial Point Processes. (R.E. Chandler) p. 29.

Moyé, L.A. Multiple Analyses in Clinical Trials. Fundamentals for Investigators. (T.A. Louis) p. 24.

Odifreddi, P. The Mathematical Century: The 30 Greatest Problems of the Last 100 Years. (M.R. Murty) p. 22.

O'Hagan, A. and Forster, J. Kendall's Advanced Theory of Statistics. Volume 2B: Bayesian Inference, 2nd edition. (M.J. Crowder) p. 44.

Pepe, M.S. The Statistical Evaluation of Medical Tests for Classification and Prediction. (V.T. Farewell) p. 49.

Porter,T.M. Karl Pearson: The Scientific Life in a Statistical Age. (D.R. Cox) p. 21.

Prigent, J.-L. Weak Convergence of Financial Markets. (F. Esche) p. 13.

Ratner, B. Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data. (D.J. Hand) p. 11.

Rausand, M. and Hoyland, A. System Reliability Theory. Models, Statistical Methods and

Applications, 2nd edition. (J.F. Lawless) p. 31. Rosenberger, W.F. and Lachin, J.M. Randomization in

Clinical Trials: Theory and Practice. (I. White) p. 6. Rowe, D.B. Multivariate Bayesian Statistics: Models for

Source Separation and Signal Unmixing. (R.W. Oldford) p. 25.

Ruppert, D. Statistics and Finance, An Introduction. (F. Trojani) p. 50.

Ruppert, D., Wand, M.P. and Carroll, R.J. Semiparametric Regression. (M.J. Crowder) p. 7.

Sahai, H. and Ojeda, M.M. Analysis of Variance for Random Models: Volume I. Balanced Data: Theory, Methods, Applications and Data Analysis. (P. Prescott) p. 46.

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