{
"item_title" : "Bayesian Inference for Probabilistic Risk Assessment",
"item_author" : [" Dana Kelly", "Curtis Smith "],
"item_description" : "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.",
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Bayesian Inference for Probabilistic Risk Assessment : A Practitioner's Guidebook
by Dana Kelly and Curtis Smith
Other Available Formats
Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9781447127086
- ISBN-10: 1447127080
- Publisher: Springer
- Publish Date: November 2013
- Dimensions: 9.21 x 6.14 x 0.51 inches
- Shipping Weight: 0.75 pounds
- Page Count: 228
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