Stochastic Modeling and Statistical Methods: Advances and Applications is the practical guide to the latest developments in data analysis and research methods. The book explores the significant research progress that has been seen in recent decades, offering vital tools for analyzing modern applications and real data. Topics covered include Dynamic Reliability, Stochastic Modeling, System Maintainability, and Parametric, Semi-Parametric, and Nonparametric Statistical Inference. Readers will find the latest advancements in these areas, making it an essential resource for researchers and practitioners who want to explore these evolving fields and stay updated on cutting-edge research.
- Presents the latest breakthroughs in Reliability Engineering, along with current perspectives on the field
- Includes shared, practical knowledge of contemporary statistical modeling techniques, thus enhancing analytical skills
- Covers the probabilistic methods used to investigate various applications in Reliability Engineering
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ISBN-13
978-0-443-31695-1 (9780443316951)
Schweitzer Klassifikation
1. Inference of one-shot devices with Weibull component lifetimes under Gamma frailty model2. Signature Reliability Detection and Performance Optimization of Low Cost Autonomous Robot Vacuum Cleaner Via-UGFT3. The vn-consistency of the empirical estimator of stationary probability of semi-Markov chains4. Alternative transient solutions for semi-Markov redundant systems in Reliability Engineering5. Parametric estimation of censored semi-Markov chains6. Understanding a system's performance in the presence of k-out-of-n: F and standby redundancy A reliability approach through Markov process7. On some occurrence rates for Markov processes with application8. Interval-censored reliability tests under lognormal lifetimes9. Selective Review of Penalized Learning Methods for Event Processes10. Hidden Markov Models for Aviation Prognostics11. Stochastic modeling of the elastic properties of carbon-fiber-reinforced 3D printed filaments using polynomial chaos expansion12. Stochastic Functionally Pooled Models for Diagnostics and Prognostics in Engineering13. The application of Drifting Markov Modelling to Dynamics Skill Acquisition14. A multi-granularity smart rejuvenation framework for a two-unit series system15. Fitting a managed population model using ABC
