Statistical Inference for Engineers and Data Scientists

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Venugopal Veeravalli Pierre MoulinCambridge University Press, 11/22/2018EAN 9781107185920, ISBN10: 1107185920Hardcover, 450 pages, 25.8 x 17.7 x 2.3 cmLanguage: EnglishThis book is a mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals. With a wealth of illustrations and examples to explain the key features of the theory and to connect with real-world applications, additional material to explore more advanced concepts, and numerous end-of-chapter problems to test the reader's knowledge, this textbook is the 'go-to' guide for learning about the core principles of statistical inference and its application in engineering and data science. The password-protected solutions manual and the image gallery from the book are available online.1. IntroductionPart I. Hypothesis Testing2. Binary hypothesis testing3. Multiple hypothesis testing4. Composite hypothesis testing5. Signal detection6. Convex statistical distances7. Performance bounds for hypothesis testing8. Large deviations and error exponents for hypothesis testing9. Sequential and quickest change detection10. Detection of random processesPart II. Estimation11. Bayesian parameter estimation12. Minimum variance unbiased estimation13. Information inequality and Cramer–Rao lower bound14. Maximum likelihood estimation15. Signal estimation. Show more