BOOK-CHAPTER

Minimum Variance Unbiased Estimation

Pierre MoulinVenugopal V. Veeravalli

Year: 2018 Cambridge University Press eBooks Pages: 280-296   Publisher: Cambridge University Press

Abstract

This 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.

Keywords:
Computer science Inference Statistical inference Key (lock) Data science Test (biology) Ideal (ethics) Variance (accounting) Statistical hypothesis testing Artificial intelligence Mathematics Statistics Epistemology Computer security

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Topics

Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability

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