Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules
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Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules
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Statistical methods for sequential hypothesis testing and changepoint detection have applications across many fields, including quality control, biomedical engineering, communication networks, econometrics, image processing, security, etc. This book presents an overview of methodology in these related areas, providing a synthesis of research from the last few decades. The methods are illustrated through real data examples, and software is referenced where possible. The emphasis is on providing all the theoretical details in a unified framework, with pointers to new research directions. Sequential Change Detection and Hypothesis Testing: General Non-i.i.d.
Book Details
- Author: Alexander Tartakovsky
- Publisher: Chapman & Hall
- eBook ISBN: 9780429531712, 0429531710
- Print ISBN: 9781032084350, 1032084359
- Other ISBNs: 1498757588, 0429155018, 9781498757584, 9780429155017
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