This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers
Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.
Ideal as a textbook...
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data.
Key features of the book include:
Comprehensive coverage of an imporant area for both research and applications.
Adopts a pragmatic...
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity...
The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers...
The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medi...
A self-contained, contemporary treatment of the analysis of long-range dependent data
Long-Memory Time Series: Theory and Methods provides an overview of the theory and methods developed to deal with long-range dependent data and describes the applications of these methodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to the analysis of methodological aspects (Estimation Methods, Asymptotic Theory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more...
A self-contained, contemporary treatment of the analysis of long-range dependent data
Long-Memory Time Series: Theory and Methods provides a...
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.
"The authors have put together an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models . . . highly recommend ed] ....
Wiley-Interscience Paperback Series
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible t...
Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer's condition, possible non-existence of some moments, and sparse observations in the tail of the distribution.
The book focuses on the methods of statistical analysis of...
Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, we...
Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.
Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level. Takes a modern approach based on mathematical, probabilistic, and graphical modeling. Provides an integrated presentation of theory, examples, exercises and applications. ...
Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It fo...
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. Levy Processes in Finance: Pricing Financial Derivatives takes a practical approach to describing the theory of Levy-based models, and features many examples of how they may be used to solve problems in finance. * Provides an introduction to the use of Levy...
Financial mathematics has recently enjoyed considerable interest on account of its impact on the finance industry. In parallel, the theory of Levy pro...
We all like to know how reliable and how risky certain situations are, and our increasing reliance on technology has led to the need for more precise assessments than ever before. Such precision has resulted in efforts both to sharpen the notions of risk and reliability, and to quantify them. Quantification is required for normative decision-making, especially decisions pertaining to our safety and wellbeing. Increasingly in recent years Bayesian methods have become key to such quantifications.
Reliability and Risk provides a comprehensive overview of the mathematical and...
We all like to know how reliable and how risky certain situations are, and our increasing reliance on technology has led to the need for more precise ...
Human health risk assessment involves the measuring of risk of exposure to disease, with a view to improving disease prevention. Mathematical, biological, statistical, and computational methods play a key role in exposure assessment, hazard assessment and identification, and dose-response modelling.
Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment is a comprehensive text that accounts for the wealth of new biological data as well as new biological, toxicological, and medical approaches adopted in risk assessment. It provides an authoritative...
Human health risk assessment involves the measuring of risk of exposure to disease, with a view to improving disease prevention. Mathematical, biologi...