Stochastic Modeling and Statistical Methods
eBook - ePub

Stochastic Modeling and Statistical Methods

Advances and Applications

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Stochastic Modeling and Statistical Methods

Advances and Applications

About this book

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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Yes, you can access Stochastic Modeling and Statistical Methods by Ioannis S. Triantafyllou,Sonia Malefaki,Alex Karagrigoriou in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Data Visualisation. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Title of Book
  2. Chapter One: Inference for one-shot devices with Weibull component lifetimes under gamma frailty model
  3. Chapter Two: Signature reliability detection and performance optimization of low-cost autonomous robot vacuum cleaner via-UGFT
  4. Chapter Three: The n-consistency of the empirical estimator of stationary probability of semi-Markov chains
  5. Chapter Four: Alternative transient solutions for semi-Markov redundant systems in reliability engineering
  6. Chapter Five: Parametric estimation of censored semi-Markov chains
  7. Chapter 6: Understanding a system's performance in the presence of k-out-of-n: F and standby redundancy: a reliability approach through Markov process
  8. Chapter Seven: On some occurrence rates for Markov processes with application
  9. Chapter Eight: Interval-censored reliability tests under lognormal lifetimes
  10. Chapter Nine: Selective review of penalized learning methods for event processes
  11. Chapter Ten: Hidden Markov model applications
  12. Chapter Eleven: Stochastic modeling of the elastic properties of carbon-fiber-reinforced 3D printed filaments using polynomial chaos expansion
  13. Chapter Twelve: Stochastic functionally pooled models for diagnostics and prognostics in engineering
  14. Chapter Thirteen: The application of drifting Markov modeling to dynamics skill acquisition
  15. Chapter Fourteen: A multi-granularity smart rejuvenation framework for a two-unit series system
  16. Chapter Fifteen: Fitting a managed population model using ABC
  17. Index