Stochastic Modeling and Statistical Methods (eBook, ePUB)

Advances and Applications
Redaktion: Triantafyllou, Ioannis S.; Karagrigoriou, Alex; Malefaki, Sonia

• Format: ePub

Produktbeschreibung

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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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 350
• Erscheinungstermin: 1. Juni 2025
• Englisch
• ISBN-13: 9780443316951
• Artikelnr.: 74733884

Inhaltsangabe

1. Inference of one-shot devices with Weibull component lifetimes under
Gamma frailty model
2. Signature Reliability Detection and Performance Optimization of Low Cost
Autonomous Robot Vacuum Cleaner Via-UGFT
3. The √n-consistency of the empirical estimator of stationary probability
of semi-Markov chains
4. Alternative transient solutions for semi-Markov redundant systems in
Reliability Engineering
5. Parametric estimation of censored semi-Markov chains
6. Understanding a system’s performance in the presence of k-out-of-n: F
and standby redundancy A reliability approach through Markov process
7. On some occurrence rates for Markov processes with application
8. Interval-censored reliability tests under lognormal lifetimes
9. Selective Review of Penalized Learning Methods for Event Processes
10. Hidden Markov Models for Aviation Prognostics
11. Stochastic modeling of the elastic properties of
carbon-fiber-reinforced 3D printed filaments using polynomial chaos
expansion
12. Stochastic Functionally Pooled Models for Diagnostics and Prognostics
in Engineering
13. The application of Drifting Markov Modelling to Dynamics Skill
Acquisition
14. A multi-granularity smart rejuvenation framework for a two-unit series
system
15. Fitting a managed population model using ABC