Chapman and Hall/CRC, August 2020
By Jianqing Fan, the Frederick L. Moore, Class of 1918, Professor in Finance, and professor of operations research and financial engineering; Runze Li, Eberly Family Chair, Pennsylvania State University; Cun-Hui Zhang, distinguished professor of statistics and biostatistics, Rutgers University; and Hui Zou, professor of statistics, University of Minnesota
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models and 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.
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