In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calc
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival
The present book analyses critically the tripartite mimicry model (consisting of the mimic, model and receiver species) and develops semiotic tools for comparative analysis. It is proposed that mimicr
Pro Spring Boot is your authoritative hands-on practical guide for increasing your Spring Framework-based enterprise Java and cloud application productivity while decreasing development time using the
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s stru
This book provides a balanced, modern introduction to Bayesian and frequentist methods for regression analysis. The author discusses Frequentist and Bayesian Inferences; Linear Models; Binary Data Mod
In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biolog
The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some r
This book provides a comprehensive, theory-based analysis of current issues in population economics. It addresses the most important problems caused by demographic changes using the popular overlappin
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development
Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated wit
Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current r
‘A Concise Introduction to the Theory of Integration’ was once a best-selling Birkhauser title which published 3 editions. This manuscript is a substantial revision of the material. Chapter one now in
Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehi
Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of sc
WINNER OF THE 2003 DEGROOT PRIZE!The DeGroot Prize is awarded every two years by the International Societyfor Bayesian Analysis in recognition of an important, timely, thorough andnotably original co
This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits.
This book provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Considerably more detail is offered than what may be warranted f
This book provides new theories, applications and quantitative methods in demography, population studies and statistics. It presents and applies data analysis, statistics and stochastic modeling techn
This book provides an introduction to elementary probability and to Bayesian mathematical statistics using de Finetti's subjectivistic approach. One of the features of this approach is that it does no
Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expans
This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers mo
This book focuses on the methodology and analysis of state and local population projections. It describes the most commonly used data sources and application techniques within each of three classes
Examines the use of newly developed analytical tools such as fuzzy logic, neural networks, simulation, and Bayesian techniques for studying uncertainty analysis in engineering, control systems, and th
This book explores the benefits of using risk analysis techniques in the evaluation of flood protection structures, and examines the results of the environmental impact assessment for selected planned
This book focuses on the methodology and analysis of state and local population projections. It describes the most commonly used data sources and application techniques for four types of projection me
This book shows the effectiveness of multiregional demography for studying the spatial dynamics of migration and population redistribution. It examines important questions in demographic analysis and
This book provides a complete analysis of educational production and costs using the nonparametric technique known as Data Envelopment Analysis (DEA). The book focuses on estimation of technical, allo
The first Bayesian Young Statisticians Meeting, BAYSM 2013, has provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and post-docs dealing with Bayesian statistics to co
This book focuses on the methodology and analysis of state and local population projections. It describes the most commonly used data sources and application techniques for four types of projection me
This book presents a new inference technique for time-evolving coupled systems in the presence of noise. It describes a way of using Bayesian inference to exploit the presence of random fluctuations,
Relevant to, and drawing from, a range of disciplines, the chapters in this collection show the diversity, and applicability, of research in Bayesian argumentation. Together, they form a challenge to
Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a moder
This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams.
This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate stude
The interest in Bayesian statistics among theoretical and applied statisticians has increased dramatically in the last few years. This classic text and reference book remains one of the most importan
This book is a comprehensive guide to qualitative comparative analysis (QCA) using R. Using Boolean algebra to implement principles of comparison used by scholars engaged in the qualitative study of
This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c
Using a series of case studies, the book demonstrates the power of dynamic analysis as applied to the fossil record. The book considers how we think about certain types of paleontological questions an
