Böcker i Wiley Series in Probability and Statistics-serien

A controversial philosophical approach to statistics following the work of Rev Thomas Bayes (1701). To solve a problem or to make a decision, the Bayesian collects data from all possible theories and assigns a probability to them. This generates a prior distribution from which, workable parameters are determined and complex calculations are made.

Finite mixture models are typically used where the population being studied is heterogeneous in composition. This work aims to offer an up-to-date account of the major issues involved with finite modelling. There is a practical emphasis on the applications of mixture models.

This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.

Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. Gives proofs of all the theoretical results used in modern sampling practice.

Structural Sensitivity in Econometric Models Edwin Kuh, John W. Neese and Peter Hollinger Provides a pathbreaking assessment of the worth of linear dynamic systems methods for probing the behavior of complex macroeconomic models.

States that research in the statistical analysis of extreme values has flourished over the years: probability models, inference and data analysis techniques have been introduced; and fresh application areas have been explored.

Presents new and up--dated material on both the underlying theory and the practical methodology of directional statistics, helping the reader to utilise and develop the techniques appropriate to their work. The book is divided into three parts. The first part concentrates on statistics on the circle.

This reference book develops a systematic process of data exploration, data cleaning and evolving a suitable modelling strategy to help analysts determine and implement a final technique.

Spatial data analysis is a fast growing area and Voronoi diagrams provide a means of naturally partitioning space into subregions to facilitate spatial data manipulation, modelling of spatial structures, pattern recognition and locational optimization.

Designed to serve as a reference for the practitioner and as a self contained textbook for the advanced student.

While mapped data provide a common ground for discussions between the public, the media, regulatory agencies, and public health researchers, the analysis of spatially referenced data has experienced a growth, thanks in part to the development of geographical information systems (GIS's).

This text provides a source for professionals in the insurance industry who have a modest level of mathematical experience. It outlines classical results and provides an insight into recent developments in applied probability theory illustrating relevant applications in insurance mathematics.

Provides practicing statisticians and econometricians with fresh tools for assessing quality and reliability of regression estimates.

Financial mathematics has recently enjoyed considerable interest on account of its impact on the finance industry. In parallel, the theory of Levy processes has also seen many exciting developments. These powerful modelling tools allow the user to model more complex phenomena, and are commonly applied to problems in finance.

Requiring no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight line regression and simple analysis of variance models, this work covers the diagnostics and methods of model fitting.

From its initial publication this book has been the standard text on the subject. Since then there has been a continuing high level of activity, and work has developed in all major areas. This third edition reflects the latest state of knowledge with fully revised and extended coverage of all topics.

The concepts of epidemiology, the science that uses statistical methods to investigate associations between risk factors and disease outcomes in human populations, are developed using examples involving real data from published studies.

The classic text for understanding complex statistical probability An Introduction to Probability Theory and Its Applications offers comprehensive explanations to complex statistical problems. Delving deep into densities and distributions while relating critical formulas, processes and approaches, this rigorous text provides a solid grounding in probability with practice problems throughout. Heavy on application without sacrificing theory, the discussion takes the time to explain difficult topics and how to use them. This new second edition includes new material related to the substitution of probabilistic arguments for combinatorial artifices as well as new sections on branching processes, Markov chains, and the DeMoivre-Laplace theorem.

Regression analysis is the study of the dependence of a response variable on one or more predictor variables. It is among the most widely used methods in statistics. In recent years, several new ways to approach regression have been presented.

A Classic adapted to modern times Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers.

Considerable changes have occurred in the field of order statistics in the nearly 20 years since "Order Statistics", second edition was published. This third edition gives a helpful account of order statistics, useful to students as well as those needing a guide to the extensive literature.

This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures.

In recent years there has been a growing interest in the application of the mathematical functions known as wavelets to a broad range of statistical problems. This pioneering, state-of-the-art book focuses on those applications.

Statistics have helped shape every area of science. Without the means to analyze critical data, none of the great disoveries of the past would be possible. This paperback reprint of a Wiley bestseller shows the development of these data analysis tools and the manner in which they aided technological development prior to 1750.

Presents methods for the design and analysis of surveys, studies, and experiments when the data is qualitative and categorical. This work also covers the delta methods for multinomial frequencies. It discusses topics in misclassification and in reliability assessment.

Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls.

Gives a treatment of data oriented techniques as well as classical methods. This sourcebook emphasizes principles rather than mathematical detail, and the coverage ranges from the practical problems of graphically representing high dimensional data to the theoretical problems relating to matrices of random variables.

This book is the first of two volumes that update Oscar Kempthorne's groundbreaking 1952 classic of the same name. This first volume is concerned primarily with the philosophical basis for experimental design and a mathematical-statistical framework within which to discuss the subject.

Converted into a paperback format, at a reduced price Markov Processes: Characterization and Convergence is ideal as a graduate text and/or reference on Markov Processes and their relationship to operator semigroups.

This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. .