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Statistical Modeling and Robust Inference for One-Shot Devices

Statistical Modeling and Robust Inference for One-Shot Devices

by Narayanaswamy Balakrishnan and Elena Castilla
Paperback
Publication Date: 08/04/2025

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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.

ISBN:
9780443141539
9780443141539
Category:
Algorithms & data structures
Format:
Paperback
Publication Date:
08-04-2025
Language:
English
Publisher:
Elsevier Science & Technology
Country of origin:
United Kingdom
Dimensions (mm):
228.6x152.4mm

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