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| 贝叶斯网络× | 统计可靠性分析× | |
|---|---|---|
| 领域≠ | 贝叶斯 | 可靠性 |
| 方法族≠ | Bayesian methods | Regression model |
| 起源年份≠ | 1988 | 1998 |
| 提出者≠ | Judea Pearl | William Meeker & Luis Escobar |
| 类型≠ | Probabilistic graphical model | Parametric lifetime modeling |
| 开创性文献≠ | Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797 | Meeker, W. Q., & Escobar, L. A. (1998). Statistical Methods for Reliability Data. Wiley. ISBN: 978-0-471-14328-4 |
| 别名≠ | Bayes network, belief network, probabilistic graphical model, directed graphical model | Life Data Analysis, Survival Analysis (Engineering), Time-to-Failure Analysis, Güvenilirlik Analizi |
| 相关≠ | 4 | 3 |
| 摘要≠ | A Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others. | Statistical reliability analysis models the time-to-failure of components, systems, or products using parametric lifetime distributions fitted to observed or censored failure data. Formalized comprehensively by William Q. Meeker and Luis A. Escobar in their 1998 Wiley monograph, the framework integrates maximum likelihood estimation, censoring mechanisms, and distributional diagnostics to produce probability-of-failure curves, hazard rates, and quantile estimates that support design, warranty, and maintenance decisions. |
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