| 期刊全称 | Bayesian Reliability | | 影响因子2023 | Michael S. Hamada,Alyson G. Wilson,Harry F. Martz | | 视频video | | | 发行地址 | Includes supplementary material: | | 学科分类 | Springer Series in Statistics | | 图书封面 |  | | 影响因子 | .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 | | Pindex | Book 2008 |
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发表于 2025-3-21 18:16:21
