Bayesian Inference for Probabilistic Risk Assessment A Practitioner's Guidebook /

• Κύριοι συγγραφείς: Kelly, Dana (Συγγραφέας), Smith, Curtis (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London, 2011.
• Σειρά: Springer Series in Reliability Engineering,
• Θέματα: Engineering.; Statistics.; Quality control.; Reliability.; Industrial safety.; Quality Control, Reliability, Safety and Risk.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemen...

Πίνακας περιεχομένων:

• 1. Introduction and Motivation
• 2. Introduction to Bayesian Inference
• 3. Bayesian Inference for Common Aleatory Models
• 4. Bayesian Model Checking
• 5. Time Trends for Binomial and Poisson Data
• 6. Checking Convergence to Posterior Distribution
• 7. Hierarchical Bayes Models for Variability
• 8. More Complex Models for Random Durations
• 9. Modeling Failure with Repair
• 10. Bayesian Treatment of Uncertain Data
• 11. Bayesian Regression Models
• 12. Bayesian Inference for Multilevel Fault Tree Models
• 13. Additional Topics.