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Contemporary Experimental Design, Multivariate Analysis and Data Mining

Festschrift in Honour of Professor Kai-Tai Fang

Jianxin Pan (Hrsg.), Jianqing Fan (Hrsg.)

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ca. 171,19
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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik

Beschreibung

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. 

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Schlagwörter

Functional data, longitudinal data, big data, variable selection, Covariance matrix, Composite design, Quantile regression, data mining, network data, 62F 62H 62G 62K 62J 62N 62P, multivariate data, high-dimensional data, Robust design, experimental design, machine learning, survival data