Book Description
This new edition of the classic statistical book Classical Inference and Relationship completes the current three-volume set of Kendall's Advanced Theory of Statistics. It has been fully revised and expanded to over 800 pages, representing the state of the art in classical statistical inference. ... Read more

Customer Reviews (1)

Beautifully Written
I've been reading the general linear model section all day today, and it is just so nicely written I thought I needed to write a review.I can't imagine a clearer and more succinct description of this difficult topic. Entirely understandable, but be prepared to read chapters from beginning toend as unexpected abbreviations are often introduced and carried throughoutthe chapter.

As with all of the Kendall Advanced Theory books, amoderate degree of mathematical sophistication is assumed. ... Read more

Customer Reviews (1)

Very elementary level text
This text was written to give a rapid introduction to the topic to statistics students who are having conceptual difficulties with the idea of more than 3 spacelike dimensions.The idea of using geometric intuition to explain the interaction of multiple variables has been very fruitful in dimensions up to 3 and can be as extended as fruitfully to collections of more than 3 variables, if the reader can first get over the intellectual hurdle that says that geometry has to have some physical referrent.This book does a very good job on that account. It doesn't go very deeply into any aspect of the topic.Prerequisites are Calculus of several variables (partial derivatives), a first course in linear algebra and high school geometry.
A prospective reader who wants a deep understanding of the subject should really read Sommerville's An introduction to the geometry of n dimensions instead.Please note that Sommerville expects a higher level of knowlege of geometry and analysis than does Kendall. ... Read more

Book Description
The Bayesian approach to statistics is now widely accepted as theoretically sound and practically viable. Enormous advances in Bayesian methodology in recent years have resulted in a great expansion of applications of Bayesian statistics in a wide variety of fields. This important addition to the series provides a comprehensive and readable treatment of modern Bayesian theory. ... Read more

Customer Reviews (1)

O'Hagan's Jewel
I found this book to be my constant reference.
Like Tonny's narative style and the part on NIG Priors!
Contains valuable contributions by the author
hard to find elsewhere.

Highly recommended! ... Read more

Book Description
This major revision contains a largely new chapter 7 providing an extensive discussion of the bivariate and multivariate versions of the standard distributions and families. Chapter 16 has been enlarged to cover multivariate sampling theory, an updated version of material previously found in the old Volume III. The previous chapters 7 and 8 have been condensed into a single chapter providing an introduction to statistical inference. Elsewhere, major updates include new material on skewness and kurtosis, hazard rate distributions, the bootstrap, the evaluation of the multivariate normal integral and ratios of quadratic forms. The new edition includes over 200 new references, 40 new exercises and 20 further examples in the main text. In addition, all the text examples have been given titles, and these are listed at the front of the book for easier reference. ... Read more

Book Description
As one of the great statisticians of the century, Sir Maurice Kendall worked in areas covering an extraordinary range from intricate theory to detailed application.This memorial selection concentrates on a number of his less well known papers.They fall into four general groups.First are
four papers concerned with applications, including his Presidential Address to the Royal Statistical Society.The next group consists of six paperson the theory of symmetric functions of sample observations.The third group includes a selection of Kendall's papers in the theory of ranking
methods, including his 1938 discovery of the rank correlation coefficient since named after him.The last group of papers contains three of his early papers on the theory of time-series. General statistical readers as well as specialists will appreciate the book's sampling of Kendall's remarkable
range of contributions. ... Read more

Book Description
The second of a two-part work on multivariate analysis, this volume covers more specialized techniques; topics include discriminant analysis, cluster analysis, path analysis, graphical modelling, latent variable techniques, repeated measures analysis and growth curve models. Modern problems and techniques, such as handling of high dimensional data and the use of neural networks are featured and the book concludes with a discussion of strategic aspects of multivariate analysis. ... Read more

Customer Reviews (2)

covers my favoirte topics in multivariate analysis
Classification is a favorite topic of Krzanowki and is one of the topics covered in this volume. This is part 2 of a volume on multivariate analysis in the Kendall's Library of Statistics series. So it has the flavor and feel of the Advanced Theory in Statistics books, a concise but almost encyclopediac treatment of advanced topics. In the first chapter on discriminant analysis (chapter 9 of this 2 volume text) time is spent describing the various methods of error rate estimation including the bootstrap and the key simulation studies of Efron, Chatterjee and Chatterjee, Snapinn and Knoke, Jain et al.,and Ganeshanandam and Krzanowski are all mentioned and referenced. There is even a section on neural networks.
The related topic of cluster analysis is covered in Chapter 10. Chapter 11 covers covariance and interaction structures that includes log-linear models, hierarchical conditional Gaussian models, path analysis and regression models. Chapter 12 covers latent structure models including factor analysis. Chapter 13 covers repeated measures and growth curve models, popular topics under a great deal of research activity lately, particularly in the pharmaceutical industry. Chapter 14 on miscellaneous topics includes shape analysis, functional data, distance measures between populations, and circular and spherical data.

nice advanced book on special topics
Classification is a favorite topic of Krzanowki and is one of the topics covered in this volume. This is part 2 of a volume on multivariate analysis in the Kendall's Library of Statistics series. So it has the flavor and feel of the Advanced Theory in Statistics books, a concise but almost encyclopediac treatment of advanced topics. In the first chapter on discriminant analysis (chapter 9 of this 2 volume text) time is spent describing the various methods of error rate estimation including the bootstrap and the key simulation studies of Efron, Chatterjee and Chatterjee, Snapinn and Knoke, Jain et al.,and Ganeshanandam and Krzanowski are all mentioned and referenced. There is even a section on neural networks.

The related topic of cluster analysis is covered in Chapter 10. Chapter 11 covers covariance and interaction structures that includes log-linear models, hierarchical conditional Gaussian models, path analysis and regression models. Chapter 12 covers latent structure models including factor analysis. Chapter 13 covers repeated measures and growth curve models, popular topics under a great deal of research activity lately, particularly in the pharmaceutical industry. Chapter 14 on miscellaneous topics includes shape analysis, functional data, distance measures between populations, and circular and spherical data. ... Read more

Book Description
The new edition of this classic reference includes a wealth of information on the mathematics and practical applications of rank correlation methods.It represents the most extensive revision since the book first appeared in 1948 and provides clear explanations of the methods of rank
correlation widely used by statisticians, educators, psychologists, and others involved in analyzing qualitative material.Among the many topics covered are the Goodman-Kruskal coefficient, partial rank correlation, trend tests, and regression techniques.Real numerical examples and problems are
taken from interesting research in the social sciences. Expanded tables have also been added that include larger sample sizes and a table of distribution of Kendall's partial law. Reflecting the vast amount of research published in recent years, this edition updates the references and offers over
300 new bibliographic entries.The valuable appendix tables have been revised and expanded. ... Read more

Book Description
Very thoroughly revised, this edition reflects developments in the fields of multivariate analysis and time-series. ... Read more

Book Description
This thorough revision of a classic text covers many new areas, including moving-average and auto-regressive moving-average schemes; estimation using transfer functions; state space models, and much more. ... Read more