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Titlebook: Contemporary Experimental Design, Multivariate Analysis and Data Mining; Festschrift in Honou Jianqing Fan,Jianxin Pan Book 2020 Springer N

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发表于 2025-3-21 18:19:19 | 显示全部楼层 |阅读模式
书目名称Contemporary Experimental Design, Multivariate Analysis and Data Mining
副标题Festschrift in Honou
编辑Jianqing Fan,Jianxin Pan
视频video
概述Gives an overview on new developments in modern statistical theories, methods and applications.Covers a wide range of important topics such as experimental design, multivariate analysis, data mining,
图书封面Titlebook: Contemporary Experimental Design, Multivariate Analysis and Data Mining; Festschrift in Honou Jianqing Fan,Jianxin Pan Book 2020 Springer N
描述.The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. .In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features four review papers on Professor Fang’s numerous contributions to the fields of experimental design, multivariate analysis, data mining and education. It also contains twenty research articles contributed by prominent and active figures in their fields. The articles cover a wide range of important topics such as experimental design, multivariate analysis, data mining, hypothesis testing and statistical models. .
出版日期Book 2020
关键词62F 62H 62G 62K 62J 62N 62P; big data; Functional data; Covariance matrix; high-dimensional data; multiva
版次1
doihttps://doi.org/10.1007/978-3-030-46161-4
isbn_softcover978-3-030-46163-8
isbn_ebook978-3-030-46161-4
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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https://doi.org/10.1007/978-81-322-1638-4l design, multivariate analysis and data mining. This paper only focuses on his contribution to experimental design. He proposed the method of visualization analysis for orthogonal designs in 1970. Inspired by three big military projects in 1978, he cooperated with Prof. Yuan Wang and proposed a new
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https://doi.org/10.1007/978-81-322-1638-4 methods to deal with large amounts of data in practical projects. By analyzing more than 400,000 pieces of data, he found representative clothing indicators and established the first adult clothing standard in China; through cleaning and modeling steel-making data from steel mills all over the coun
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Facial Expressions of Emotions: ,,ncement of statistics in China. Under his leadership, his team had completed some of the China’s hallmark industrial projects through novel applications of statistics and developments of new statistical methodologies. He has authored/coauthored a series of best-selling modern statistics textbooks, t
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Urban Transportation Trends: An Overview,ing that the OofA experiment involves . components, there are .! different orders of adding sequence. When . is large, it is infeasible to compare all .! possible solutions (for example, . millions). Two potential construction methods are systematic combinatorial construction and computer algorithmi
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Sugata Marjit,Vivekananda Mukherjeen dependence on the unknown parameters. This article considers the robust designs for Poisson mixed models. Given the prior knowledge of the fixed effects parameters, a modification of the two robust design criteria is proposed by applying the number-theoretic methods. The simulated annealing algori
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