Bayesian Inference And Computation In Reliability And Survival Analysis
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Bayesian Inference And Computation In Reliability And Survival Analysis
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Author : Yuhlong Lio
language : en
Publisher: Springer Nature
Release Date : 2022-08-01
Bayesian Inference And Computation In Reliability And Survival Analysis written by Yuhlong Lio and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-01 with Mathematics categories.
Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research.
Reliability And Risk
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Author : Nozer D. Singpurwalla
language : en
Publisher: John Wiley & Sons
Release Date : 2006-08-14
Reliability And Risk written by Nozer D. Singpurwalla and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-14 with Mathematics categories.
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 statistical aspects of risk and reliability analysis, from a Bayesian perspective. This book sets out to change the way in which we think about reliability and survival analysis by casting them in the broader context of decision-making. This is achieved by: Providing a broad coverage of the diverse aspects of reliability, including: multivariate failure models, dynamic reliability, event history analysis, non-parametric Bayes, competing risks, co-operative and competing systems, and signature analysis. Covering the essentials of Bayesian statistics and exchangeability, enabling readers who are unfamiliar with Bayesian inference to benefit from the book. Introducing the notion of “composite reliability”, or the collective reliability of a population of items. Discussing the relationship between notions of reliability and survival analysis and econometrics and financial risk. Reliability and Risk can most profitably be used by practitioners and research workers in reliability and survivability as a source of information, reference, and open problems. It can also form the basis of a graduate level course in reliability and risk analysis for students in statistics, biostatistics, engineering (industrial, nuclear, systems), operations research, and other mathematically oriented scientists, wherein the instructor could supplement the material with examples and problems.
Bayesian Survival Analysis
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Author : Joseph G. Ibrahim
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Bayesian Survival Analysis written by Joseph G. Ibrahim and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Medical categories.
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 analysis. It presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all from the health sciences, including cancer, AIDS, and the environment.
Bayesian Survival Analysis
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Author : Joseph G. Ibrahim
language : en
Publisher:
Release Date : 2014-01-15
Bayesian Survival Analysis written by Joseph G. Ibrahim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Reliability And Survival Analysis
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Author : Md. Rezaul Karim
language : en
Publisher: Springer
Release Date : 2019-08-09
Reliability And Survival Analysis written by Md. Rezaul Karim and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-09 with Medical categories.
This book presents and standardizes statistical models and methods that can be directly applied to both reliability and survival analysis. These two types of analysis are widely used in many fields, including engineering, management, medicine, actuarial science, the environmental sciences, and the life sciences. Though there are a number of books on reliability analysis and a handful on survival analysis, there are virtually no books on both topics and their overlapping concepts. Offering an essential textbook, this book will benefit students, researchers, and practitioners in reliability and survival analysis, reliability engineering, biostatistics, and the biomedical sciences.
Bayesian Thinking Modeling And Computation
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Author :
language : en
Publisher: Elsevier
Release Date : 2005-11-29
Bayesian Thinking Modeling And Computation written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-29 with Mathematics categories.
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians. Critical thinking on causal effects Objective Bayesian philosophy Nonparametric Bayesian methodology Simulation based computing techniques Bioinformatics and Biostatistics
Bayesian Reliability Analysis
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Author : Harry F. Martz
language : en
Publisher:
Release Date : 1982-05-14
Bayesian Reliability Analysis written by Harry F. Martz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-05-14 with Mathematics categories.
A comprehensive collection of and introduction to the major advances in Bayesian reliability analysis techniques developed during the last two decades, in textbook form. Focuses primary attention on the exponential, Weibull, normal, log normal, inverse Gaussian, and gamma failure time distributions, as well as the binomial, Pascal, and Poisson sampling models. Noninformative and natural conhugate prior distributions are emphasized, although other classes or prior distributions are also often considered. Background chapters on probability, statistics, and classical reliability analysis methods are also included.
Recent Advances In Reliability Theory
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Author : N. Limnios
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Recent Advances In Reliability Theory written by N. Limnios and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
This book presents thirty-one extensive and carefully edited chapters providing an up-to-date survey of new models and methods for reliability analysis and applications in science, engineering, and technology. The chapters contain broad coverage of the latest developments and innovative techniques in a wide range of theoretical and numerical issues in the field of statistical and probabilistic methods in reliability.
Reliability And Decision Making
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Author : Richard E. Barlow
language : en
Publisher: CRC Press
Release Date : 1993-09-01
Reliability And Decision Making written by Richard E. Barlow and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-09-01 with Business & Economics categories.
First published in 1993. Routledge is an imprint of Taylor & Francis, an informa company.
Bayesian Statistics And Its Applications
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Author : Satyanshu K. Upadhyay
language : en
Publisher: Anshan Pub
Release Date : 2007
Bayesian Statistics And Its Applications written by Satyanshu K. Upadhyay and has been published by Anshan Pub this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
In the last two decades, Bayesian Statistics has acquired immense importance and has penetrated almost every area including those where the application of statistics appeared to be a remote possibility. This volume provides both theoretical and practical insights into the subject with detailed up-to-date material on various aspects. It serves two important objectives - to offer a thorough background material for theoreticians and gives a variety of applications for applied statisticians and practitioners. Consisting of 33 chapters, it covers topics on biostatistics, econometrics, reliability, image analysis, Bayesian computation, neural networks, prior elicitation, objective Bayesian methodologies, role of randomisation in Bayesian analysis, spatial data analysis, nonparametrics and a lot more. The book will serve as an excellent reference work for updating knowledge and for developing new methodologies in a wide variety of areas. It will become an invaluable tool for statisticians and the practitioners of Bayesian paradigm.