Search results for ""Author George A. F. Seber""

A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and statistical theory, this handbook is organized by topic rather than mathematical developments and includes numerous references to both the theory behind the methods and the applications of the methods. A uniform approach is applied to each chapter, which contains four parts: a definition followed by a list of results; a short list of references to related topics in the book; one or more references to proofs; and references to applications. The use of extensive cross-referencing to topics within the book and external referencing to proofs allows for definitions to be located easily as well as interrelationships among subject areas to be recognized. A Matrix Handbook for Statisticians addresses the need for matrix theory topics to be presented together in one book and features a collection of topics not found elsewhere under one cover. These topics include: Complex matrices A wide range of special matrices and their properties Special products and operators, such as the Kronecker product Partitioned and patterned matrices Matrix analysis and approximation Matrix optimization Majorization Random vectors and matrices Inequalities, such as probabilistic inequalities Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumes a fundamental knowledge of vectors and matrices, maintains a reasonable level of abstraction when appropriate, and provides a comprehensive compendium of linear algebra results with use or potential use in statistics. A Matrix Handbook for Statisticians is an essential, one-of-a-kind book for graduate-level courses in advanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves as an excellent self-study guide for statistical researchers.

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Text combines lucid and statistically engaging exposition, graphic and poignantly applied examples, realistic exercise settings to take student past the mechanics of introductory-level statistical techniques into the realm of practical data analysis and inference-based problem solving.

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Concise, mathematically clear, and comprehensive treatment of the subject. * Expanded coverage of diagnostics and methods of model fitting. * Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models. * More than 200 problems throughout the book plus outline solutions for the exercises. * This revision has been extensively class-tested.

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Offering a viable solution to the long-standing problem ofestimating the abundance of rare, clustered populations, adaptivesampling designs are rapidly gaining prominence in the natural andsocial sciences as well as in other fields with inherentlydifficult sampling situations. In marked contrast to conventionalsampling designs, in which the entire sample of units to beobserved is fixed prior to the survey, adaptive sampling strategiesallow for increased sampling intensity depending upon observationsmade during the survey. For example, in a survey to assess theabundance of a rare animal species, neighboring sites may be addedto the sample whenever the species is encountered during thesurvey. In an epidemiological survey of a contagious or geneticallylinked disease, sampling intensity may be increased wheneverprevalence of the disease is encountered. Written by two acknowledged experts in this emerging field, thisbook offers researchers their first comprehensive introduction toadaptive sampling. An ideal reference for statisticians conductingresearch in survey designs and spatial statistics as well asresearchers working in the environmental, ecological, publichealth, and biomedical sciences. Adaptive Sampling: * Provides a comprehensive, fully integrated introduction toadaptive sampling theory and practice * Describes recent research findings * Introduces readers to a wide range of adaptive samplingstrategies and techniques * Includes numerous real-world examples from environmentalpollution studies, surveys of rare animal and plant species,studies of contagious diseases, marketing surveys, mineral andfossil-fuel assessments, and more

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WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of Nonlinear Regression "A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; and I would imagine that any statistician concerned with nonlinear regression would want a copy on his shelves." –The Statistician "Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher." –Mathematical Reviews

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