Statistical Modeling and Robust Inference for One-shot Devices - Narayanaswamy Balakrishnan, Elena Castilla

Statistical Modeling and Robust Inference for One-shot Devices

Buch | Softcover
250 Seiten
2025
Academic Press Inc (Verlag)
978-0-443-14153-9 (ISBN)
169,95 inkl. MwSt
Statistical Modeling and Robust Interference for One-shot Devices offers a comprehensive investigation on robust techniques for one-shot devices under accelerated life tests. With numerous examples, case studies, and included R codes in each chapter, this book helps readers implement their own codes, use them in proposed examples, and conduct their own research on one-shot device testing data. Researchers, mathematicians, engineers, and students working on accelerated life testing data analysis and robust methodologies will surely find this to be a welcomed resource. The study of one-shot devices such as automobile airbags, fire extinguishers, and antigen tests is rapidly becoming an important problem in the area of reliability engineering. These devices, which get destroyed or must be rebuilt after use, are particular cases of extreme censoring, which makes the problem of estimating their reliability and lifetime challenging. As classical statistical and inferential methods do not consider the issue of robustness, this book is a welcomed addition to the conversation.

Narayanaswamy Balakrishnan is a distinguished university professor in the Department of Mathematics and Statistics at McMaster University Hamilton, Ontario, Canada. He is an internationally recognized expert on statistical distribution theory, and a book-powerhouse with over 24 authored books, four authored handbooks, and 30 edited books under his name. He is currently the Editor-in-Chief of Communications in Statistics published by Taylor & Francis. He was also the Editor-in-Chief for the revised version of Encyclopedia of Statistical Sciences published by John Wiley & Sons. He is a Fellow of the American Statistical Association and a Fellow of the Institute of Mathematical Statistics. In 2016, he was awarded an Honorary Doctorate from The National and Kapodistrian University of Athens, Athens, Greece. In 2021, he was elected as a Fellow of the Royal Society of Canada. Elena Castilla is an assistant professor at the Department of Applied Mathematics at Rey Juan Carlos University, in Spain. She obtained her Ph.D, M.Sc. and Bachelor Degrees in Mathematics and Statistics at Universidad Complutense de Madrid, and is an awardee of the Ramiro Melendreras Award (SEIO, 2021) and Vicent Caselles Award (RSME & Fundación BBVA 2022). Dr. Castilla’s research interests include information theory, categorical data analysis, composite likelihood, logistic regression models, reliability analysis and robust statistics.

1. Introduction 2. Preliminaries 3. Divergence Measures and their Application to One-shot Device Testing 4. Robust Inference under the Exponential Distribution 5. Robust Inference under the Gamma Distribution 6. Robust Inference under the Weibull Distribution 7. Robust Inference under the Lognormal distribution 8. Robust Inference under the Proportional Hazards Model 9. Robust Inference under the Exponential Distribution and Competing Risks 10. Robust Inference under the Weibull Distribution and Competing Risks 11. Robust Optimal Design of Accelerated Life Tests for One-Shot Device Testing 12. Conclusions and Future Directions

Erscheint lt. Verlag 1.4.2025
Verlagsort San Diego
Sprache englisch
Maße 152 x 229 mm
Themenwelt Informatik Theorie / Studium Algorithmen
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
ISBN-10 0-443-14153-3 / 0443141533
ISBN-13 978-0-443-14153-9 / 9780443141539
Zustand Neuware
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