Statistical Foundations of Data Science (Hardcover)
暫譯: 數據科學的統計基礎 (精裝版)
Fan, Jianqing, Li, Runze, Zhang, Cun-Hui
- 出版商: CRC
- 出版日期: 2020-08-17
- 售價: $4,200
- 貴賓價: 9.5 折 $3,990
- 語言: 英文
- 頁數: 774
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1466510846
- ISBN-13: 9781466510845
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相關分類:
Data Science
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相關主題
商品描述
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.
The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
商品描述(中文翻譯)
《數據科學的統計基礎》提供了對常用統計模型、當代統計機器學習技術和算法的全面介紹，並探討其數學見解和統計理論。該書旨在作為研究生級別的教科書和高維統計、稀疏性與協方差學習、機器學習及統計推斷的研究專著。書中包含大量的練習題，涵蓋理論研究和實證應用。
本書首先介紹大數據的典型特徵及其對統計分析的影響。接著介紹多元線性回歸，並通過非參數回歸和核技巧擴展模型構建技術。它全面闡述了稀疏性探索和多元回歸、廣義線性模型、分位數回歸、穩健回歸、風險回歸等模型選擇的過程。高維推斷和特徵篩選也得到了充分的探討。該書還全面介紹了高維協方差估計、潛在因子和隱藏結構的學習，以及它們在統計估計、推斷、預測和機器學習問題中的應用。此外，書中還詳細介紹了統計機器學習理論和分類、聚類及預測的方法，包括CART、隨機森林、提升法、支持向量機、聚類算法、稀疏主成分分析和深度學習。
作者簡介
The authors are international authorities and leaders on the presented topics. All are fellows of the Institute of Mathematical Statistics and the American Statistical Association.
Jianqing Fan is Frederick L. Moore Professor, Princeton University. He is co-editing Journal of Business and Economics Statistics and was the co-editor of The Annals of Statistics, Probability Theory and Related Fields, and Journal of Econometrics and has been recognized by the 2000 COPSS Presidents' Award, AAAS Fellow, Guggenheim Fellow, Guy medal in silver, Noether Senior Scholar Award, and Academician of Academia Sinica.
Runze Li is Elberly family chair professor and AAAS fellow, Pennsylvania State University, and was co-editor of The Annals of Statistics.
Cun-Hui Zhang is distinguished professor, Rutgers University and was co-editor of Statistical Science.
Hui Zou is professor, University of Minnesota and was action editor of Journal of Machine Learning Research.
作者簡介(中文翻譯)
作者們是所呈現主題的國際權威和領導者。所有人均為數學統計學會（Institute of Mathematical Statistics）和美國統計學會（American Statistical Association）的會士。
**范建清**（Jianqing Fan）是普林斯頓大學（Princeton University）的弗雷德里克·L·摩爾教授（Frederick L. Moore Professor）。他是《商業與經濟統計期刊》（Journal of Business and Economics Statistics）的共同編輯，曾擔任《統計年鑑》（The Annals of Statistics）、《概率論及相關領域》（Probability Theory and Related Fields）和《計量經濟學期刊》（Journal of Econometrics）的共同編輯，並獲得2000年COPSS總統獎（COPSS Presidents' Award）、美國科學促進會（AAAS）會士、古根海姆獎學金（Guggenheim Fellow）、銀獎蓋伊獎（Guy medal in silver）、諾特獎學者（Noether Senior Scholar Award）以及中央研究院（Academia Sinica）院士。
**李潤澤**（Runze Li）是賓州州立大學（Pennsylvania State University）的艾爾伯利家族講座教授（Elberly family chair professor）和美國科學促進會（AAAS）會士，曾擔任《統計年鑑》（The Annals of Statistics）的共同編輯。
**張存輝**（Cun-Hui Zhang）是羅格斯大學（Rutgers University）的傑出教授（distinguished professor），曾擔任《統計科學》（Statistical Science）的共同編輯。
**鄒輝**（Hui Zou）是明尼蘇達大學（University of Minnesota）的教授，曾擔任《機器學習研究期刊》（Journal of Machine Learning Research）的行動編輯。
