New York: Routledge, 2025. - 170 p. - ISBN 1032744006. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis...
Springer, 2024. — 237 p. This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications. These spatial variables fall into three categories: continuous, like terrain elevation; events, like tree locations; and mosaics, like medical images. Definitions and discussions of random field models...
2nd edition. — Springer, 2024. — 261 p. This book describes how Bayesian methods work. Aiming to demystify the approach, it explains how to parameterize and compare models while accounting for uncertainties in data, model parameters and model structures. Bayesian thinking is not difficult and can be used in virtually every kind of research. How exactly should data be used in...
Москва: Наука, Главная редакция физико-математической литературы, 1989. — 328 с. — ISBN 5020141038. Описывается современное состояние прикладной теории байесовского статистического оценивания. Особое внимание уделяется непараметрическим методам и способам выбора априорного распределения. Исследуется ряд новых типов байесовских оценок: квазипараметрические оценки, байесовские...
New York: Springer, 2002. — 440 p. The 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24-25, 1999. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the three...
New York: Springer, 1999. — 435 p. The 4th Workshop on Case Studies in Bayesian Statistics was held at the Car negie Mellon University campus on September 27-28, 1997. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the four...
New York: Springer, 1997. — 482 p. Like the first two volumes, this third volume of case studies presents detailed applications of Bayesian statistical analysis, emphasizing the sci entific context. The papers were presented and discussed at a workshop at Carnegie Mellon University, October 5-7, 1995. In this volume, which is dedicated to the memory of Morris H. DeGroot,...
New York: Springer, 1995. — 376 p. Like its predecessor, this second volume presents detailed applications of Bayesian statistical analysis, each of which emphasizes the scientific context of the problems it attempts to solve. The emphasis of this volume is on biomedical applications. These papers were presented at a workshop at Carnegie-Mellon University in 1993. Front Matter...
New York: Springer, 1993. — 445 p. The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to...
World Scientific Publishing, 2024. — 380 p. — eBook ISBN 978-981-12-8492-2. Bayesian analysis is today understood to be an extremely powerful method of statistical analysis, as well an approach to statistics that is particularly transparent and intuitive. It is thus being extensively and increasingly utilized in virtually every area of science and society that involves analysis...
World Scientific Publishing, 2024. — 380 p. — ISBN 978-981-12-8492-2(eBook). Bayesian analysis is today understood to be an extremely powerful method of statistical analysis, as well an approach to statistics that is particularly transparent and intuitive. It is thus being extensively and increasingly utilized in virtually every area of science and society that involves...
Boca Raton: CRC Press, 2024. — 347 p. Preface Introduction Bayesian Modelling Statistical Model Bayes Model Advantages Sequential Analysis Big Data Hierarchical Models List of Problems Choice of Prior Subjective Priors Conjugate Priors Non-informative Priors Laplace Prior Jeffreys Prior Reference Priors List of Problems Decision Theory Basics of Decision Theory Bayesian...
Without authors. — The Open University, 2007. — 36 p. M249 Practical modern statistics uses the software packages IBM SPSS Statistics (SPSS Inc.) and Win BUGS, and other software. This software is provided as part of the module, and its use is covered in the Introduction to statistical modeling and in the four computer books associated with Books 1 to 4. This publication forms...
Amsterdam: Elsever, 1985. — 390 p. — ISBN 0444877460. Proceeding of the Second Valencia International Meeting. The Second Valencia International Meeting on Bayesian Statistics took place from 6-10 September, 1983, at the Hotel Las Fuentes, Alcoceber, 100 kms north of Valencia, Spain, where the first such meeting had been held four years previously. As on that first occasion,...
New York: Thomas Y. Crowell Company, 1975. — 455 p. Over the past few years I have been encouraged by colleagues and students who knew of my interest in Bayesian statistics to write a book that would explain the Bayesian approach in reasonably simple language, and would serve as a practical guide to carrying out Bayesian analyses. This book is the result. It attempts to...
Springer, 2024. — 493 p. — (International Series in Operations Research & Management Science 352). — ISBN 978-3-031-48207-6. This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions...
Pearson Education, Inc., 2023. — 192 p. — ISBN-13 978-0-13-758098-9. Leverage the Full Power of Bayesian Analysis for Competitive Advantage Bayesian methods can solve problems you can't reliably handle any other way. Building on your existing Excel analytics skills and experience, Microsoft Excel MVP Conrad Carlberg helps you make the most of Excel's Bayesian capabilities and...
3rd ed. — Birmingham: Packt Publishing, 2024. — 392 p. — ISBN 1805127160. Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries. Key Features Conduct Bayesian data analysis with step-by-step guidance Gain insight into a modern,...
ITexLi, 2024. — 78 p. — ISBN 1837693552 9781837693559 1837693560 9781837693566 1837693579 9781837693573. This book is an invaluable resource for anyone interested in the intersection of statistics, machine learning, and data science. It offers a unique perspective on Bayesian inference, revealing its potential to provide robust solutions in an increasingly data-driven world....
Учебное пособие. — Перевод с англ. А.А. Рывкина. — М.: Финансы и статистика, 1987. — 335 с. В современном статистическом анализе существует два подхода: частотный и байесовский. Согласно байесовской теории, случайность определяется как мера нашего незнания, и такая интерпретация возможна почти у каждого случайного процесса. Книга об альтернативном методе в статистике и теории...
SAGE Publications Ltd., 2022. — 272 p. — ISBN 978-1-5297-6861-9. This book walks you through learning probability and statistics from a Bayesian point of view. From an introduction to probability theory through to frameworks for doing rigorous calculations of probability, it discusses Bayes’ Theorem before illustrating how to use it in a variety of different situations with...
SAGE Publications Ltd., 2022. — 272 p. — ISBN 978-1-5297-6861-9. This book walks you through learning probability and statistics from a Bayesian point of view. From an introduction to probability theory through to frameworks for doing rigorous calculations of probability, it discusses Bayes’ Theorem before illustrating how to use it in a variety of different situations with...
SAGE Publications Ltd., 2022. — 272 p. — ISBN 978-1-5297-6861-9. This book walks you through learning probability and statistics from a Bayesian point of view. From an introduction to probability theory through to frameworks for doing rigorous calculations of probability, it discusses Bayes’ Theorem before illustrating how to use it in a variety of different situations with...