Download or read book System And Bayesian Reliability Essays In Honor Of Professor Richard E Barlow On His 70th Birthday written by Yu Hayakawa and published by World Scientific. This book was released on 2001-12-21 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of articles on reliability systems and Bayesian reliability analysis. Written by reputable researchers, the articles are self-contained and are linked with literature reviews and new research ideas. The book is dedicated to Emeritus Professor Richard E Barlow, who is well known for his pioneering research on reliability theory and Bayesian reliability analysis.
Download or read book Bayesian Statistics 7 written by J. M. Bernardo and published by Oxford University Press. This book was released on 2003-07-03 with total page 1114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the 7th Valencia International Meeting on Bayesian Statistics. This conference is held every four years and provides the main forum for researchers in the area of Bayesian statistics to come together to present and discuss frontier developments in the field.
Download or read book Stochastic Ageing and Dependence for Reliability written by Chin Diew Lai and published by Springer Science & Business Media. This book was released on 2006-09-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a panoramic view of theory and applications of Ageing and Dependence in the use of mathematical methods in reliability and survival analysis. Ageing and dependence are important characteristics in reliability and survival analysis. They affect decisions with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas. Most of the works containing the topics covered here are theoretical in nature. However, this book offers applications, exercises, and examples. It serves as a reference for professors and researchers involved in reliability and survival analysis.
Download or read book Statistical Advances in the Biomedical Sciences written by Atanu Biswas and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool for medical researchers, statisticians, public health professionals, and biostatisticians.
Download or read book Autonomic and Trusted Computing written by Bing Xie and published by Springer Science & Business Media. This book was released on 2010-10-08 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing systems including hardware, software, communication, and networks are becoming increasingly large and heterogeneous. In short, they have become - creasingly complex. Such complexity is getting even more critical with the ubiquitous permeation of embedded devices and other pervasive systems. To cope with the growing and ubiquitous complexity, autonomic computing (AC) focuses on self-manageable computing and communication systems that exhibit self-awareness, self-configuration, self-optimization, self-healing, self-protection and other self-* properties to the maximum extent possible without human intervention or guidance. Organic computing (OC) additionally addresses adaptability, robustness, and c- trolled emergence as well as nature-inspired concepts for self-organization. Any autonomic or organic system must be trustworthy to avoid the risk of losing control and retain confidence that the system will not fail. Trust and/or distrust relationships in the Internet and in pervasive infrastructures are key factors to enable dynamic interaction and cooperation of various users, systems, and services. Trusted/ trustworthy computing (TC) aims at making computing and communication systems––as well as services––available, predictable, traceable, controllable, asse- able, sustainable, dependable, persistent, security/privacy protectable, etc. A series of grand challenges exists to achieve practical autonomic or organic s- tems with truly trustworthy services. Started in 2005, ATC conferences have been held at Nagasaki (Japan), Vienna (Austria), Three Gorges (China), Hong Kong (China), Oslo (Norway) and Brisbane (Australia). The 2010 proceedings contain the papers presented at the 7th International Conference on Autonomic and Trusted Computing (ATC 2010), held in Xi’an, China, October 26–29, 2010.
Download or read book Modern Biostatistical Methods for Evidence Based Global Health Research written by Ding-Geng (Din) Chen and published by Springer Nature. This book was released on 2022-11-25 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the emerging topics in biostatistical theories and methods through their applications to evidence-based global health research and decision-making. It brings together some of the top scholars engaged in biostatistical method development on global health to highlight and describe recent advances in evidence-based global health applications. The volume is composed of five main parts: data harmonization and analysis; systematic review and statistical meta-analysis; spatial-temporal modeling and disease mapping; Bayesian statistical modeling; and statistical methods for longitudinal data or survival data. It is designed to be illuminating and valuable to both expert biostatisticians and to health researchers engaged in methodological applications in evidence-based global health research. It is particularly relevant to countries where global health research is being rigorously conducted.
Download or read book Mathematical Reviews written by and published by . This book was released on 2003 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2004 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The British National Bibliography written by Arthur James Wells and published by . This book was released on 2002 with total page 1190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Subject Guide to Books in Print written by and published by . This book was released on 1997 with total page 3310 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Books in Print Supplement written by and published by . This book was released on 2002 with total page 2576 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Reliability written by Michael S. Hamada and published by Springer Science & Business Media. This book was released on 2008-08-15 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 science and engineering have significantly increased over the past few decades. This increase is largely due to advances in simulation-based computational tools for implementing Bayesian methods. The authors extensively use such tools throughout this book, focusing on assessing the reliability of components and systems with particular attention to hierarchical models and models incorporating explanatory variables. Such models include failure time regression models, accelerated testing models, and degradation models. The authors pay special attention to Bayesian goodness-of-fit testing, model validation, reliability test design, and assurance test planning. Throughout the book, the authors use Markov chain Monte Carlo (MCMC) algorithms for implementing Bayesian analyses -- algorithms that make the Bayesian approach to reliability computationally feasible and conceptually straightforward. This book is primarily a reference collection of modern Bayesian methods in reliability for use by reliability practitioners. There are more than 70 illustrative examples, most of which utilize real-world data. This book can also be used as a textbook for a course in reliability and contains more than 160 exercises. Noteworthy highlights of the book include Bayesian approaches for the following: Goodness-of-fit and model selection methods Hierarchical models for reliability estimation Fault tree analysis methodology that supports data acquisition at all levels in the tree Bayesian networks in reliability analysis Analysis of failure count and failure time data collected from repairable systems, and the assessment of various related performance criteria Analysis of nondestructive and destructive degradation data Optimal design of reliability experiments Hierarchical reliability assurance testing
Download or read book Practical Applications of Bayesian Reliability written by Yan Liu and published by John Wiley & Sons. This book was released on 2019-05-28 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodology Educates managers on the potential of Bayesian reliability models and associated impact Introduces commonly used predictive reliability models and advanced Bayesian models based on real life applications Includes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studies JAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance.
Download or read book Inference for the Exponential Life Distribution written by Richard E. Barlow and published by . This book was released on 1979 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper constitutes Chapter 1 of a book on 'Inference and Data Analysis for Reliability and Life Testing.' The purpose is to provide an elementary coherent Bayesian foundation for research in statistical reliability theory. The results in Section 3 and the Appendix concerning the role of failures and total time on test in statistical inference for the exponential model is new. (Author).
Download or read book Reliability and Risk written by Nozer D. Singpurwalla and published by John Wiley & Sons. This book was released on 2006-08-14 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Theory and Applications of Reliability With Emphasis on Bayesian and Nonparametric Methods written by Chris Tsokos and published by Elsevier. This book was released on 2012-12-02 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Theory and Applications of Reliability: With Emphasis on Bayesian and Nonparametric Methods, Volume I covers the proceedings of the conference on ""The Theory and Applications of Reliability with Emphasis on Bayesian and Nonparametric Methods."" The conference is organized so as to have technical presentations, a clinical session, and round table discussions. This volume is a 29-chapter text that specifically deals with the theoretical aspects of reliability estimation. Considerable chapters on the technical sessions are devoted to initial findings on the theory and applications of reliability estimation, with special emphasis on Bayesian and nonparametric methods. A Bayesian analysis implies the use of suitable prior information in association with Bayes theorem while the nonparametric approach analyzes the reliability components and systems under the assumption of a time-to-failure distribution with a wide defining property rather than a specific parametric class of probability distributions. The clinical session chapters discuss the actual problems encountered in reliability estimation. The remaining chapters deal with the status of the subject areas and the empirical Bayes developments. These chapters also present various probabilistic and statistic methods for reliability estimation. Theoreticians and reliability engineers will find this book invaluable.
Download or read book Bayesian Reliability Analysis written by Harry F. Martz and published by . This book was released on 1982-05-14 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
