Statistical Inference for Engineers and Data Scientists (Hardcover)
Moulin, Pierre, Veeravalli, Venugopal V.
- 出版商: Cambridge
- 出版日期: 2019-01-24
- 售價: $1,480
- 貴賓價: 9.8 折 $1,450
- 語言: 英文
- 頁數: 418
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1107185920
- ISBN-13: 9781107185920
-
相關分類:
Data Science
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商品描述
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.
商品描述(中文翻譯)
這本書是一本數學上易於理解且最新的介紹,旨在提供解決工程和數據科學中現代推斷問題所需的工具。適合修讀統計推斷、檢測和估計課程的研究生,也是研究人員和專業人士的寶貴參考資料。書中豐富的插圖和例子用於解釋理論的關鍵特點並與實際應用相連,還提供了進一步探索高級概念的額外材料,以及眾多章末問題來測試讀者的知識。這本教科書是學習統計推斷的核心原則及其在工程和數據科學中應用的首選指南。書中的密碼保護解答手冊和圖片庫可在線上獲得。
作者簡介
Pierre Moulin, University of Illinois, Urbana-Champaign
Pierre Moulin is a professor in the ECE Department at the University of Illinois, Urbana-Champaign. His research interests include statistical inference, machine learning, detection and estimation theory, information theory, statistical signal, image, and video processing, and information security. Moulin is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), and served as a Distinguished Lecturer for the IEEE Signal Processing Society. He has received two best paper awards from the IEEE Signal Processing Society and the US National Science Foundation CAREER Award. He was founding Editor-in-Chief of the IEEE Transactions on Information Security and Forensics.
Venugopal V. Veeravalli, University of Illinois, Urbana-Champaign
Venugopal V. Veeravalli is the Henry Magnuski Professor in the ECE Department at the University of Illinois, Urbana-Champaign. His research interests include statistical inference and machine learning, detection and estimation theory, and information theory, with applications to data science, wireless communications and sensor networks. Veeravalli is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), and served as a Distinguished Lecturer for the IEEE Signal Processing Society. Among the awards he has received are the IEEE Browder J. Thompson Best Paper Award, the National Science Foundation CAREER Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), and the Wald Prize in Sequential Analysis.
作者簡介(中文翻譯)
Pierre Moulin,伊利諾伊大學香檳分校的教授。他的研究興趣包括統計推斷、機器學習、檢測和估計理論、信息理論、統計信號、圖像和視頻處理以及信息安全。Moulin是電氣和電子工程師學會(IEEE)的會士,曾擔任IEEE信號處理學會的傑出講師。他曾獲得IEEE信號處理學會和美國國家科學基金會兩項最佳論文獎,並獲得了美國國家科學基金會職業生涯獎。他曾擔任IEEE信息安全和取證交易的創刊主編。
Venugopal V. Veeravalli,伊利諾伊大學香檳分校的Henry Magnuski教授。他的研究興趣包括統計推斷和機器學習、檢測和估計理論、信息理論,以及在數據科學、無線通信和感測器網絡等領域的應用。Veeravalli是電氣和電子工程師學會(IEEE)的會士,曾擔任IEEE信號處理學會的傑出講師。他曾獲得IEEE Browder J. Thompson最佳論文獎、美國國家科學基金會職業生涯獎、總統早期科學家和工程師獎(PECASE),以及順序分析的Wald獎。
目錄大綱
1. Introduction
Part I. Hypothesis Testing:
2. Binary hypothesis testing
3. Multiple hypothesis testing
4. Composite hypothesis testing
5. Signal detection
6. Convex statistical distances
7. Performance bounds for hypothesis testing
8. Large deviations and error exponents for hypothesis testing
9. Sequential and quickest change detection
10. Detection of random processes
Part II. Estimation:
11. Bayesian parameter estimation
12. Minimum variance unbiased estimation
13. Information inequality and Cramer–Rao lower bound
14. Maximum likelihood estimation
15. Signal estimation.
目錄大綱(中文翻譯)
1. 簡介
第一部分. 假設檢定:
2. 二元假設檢定
3. 多重假設檢定
4. 複合假設檢定
5. 信號檢測
6. 凸統計距離
7. 假設檢定的性能界限
8. 假設檢定的大偏差和錯誤指數
9. 連續和最快變化檢測
10. 隨機過程的檢測
第二部分. 估計:
11. 貝葉斯參數估計
12. 最小方差無偏估計
13. 資訊不等式和Cramer-Rao下界
14. 最大概似估計
15. 信號估計。