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Titlebook: Principal Component Analysis and Randomness Test for Big Data Analysis; Practical Applicatio Mieko Tanaka-Yamawaki,Yumihiko Ikura Book 2023

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書目名稱Principal Component Analysis and Randomness Test for Big Data Analysis
副標(biāo)題Practical Applicatio
編輯Mieko Tanaka-Yamawaki,Yumihiko Ikura
視頻videohttp://file.papertrans.cn/756/755294/755294.mp4
概述Presents a practical method to use PCA and randomness measure based on the RMT formula.Proposes a new and universal approach of big data analysis irrelevant to the details of data types or fields.Uses
叢書名稱Evolutionary Economics and Social Complexity Science
圖書封面Titlebook: Principal Component Analysis and Randomness Test for Big Data Analysis; Practical Applicatio Mieko Tanaka-Yamawaki,Yumihiko Ikura Book 2023
描述.This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the "meaning" of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors‘ approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science.. . First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series,?.C?.=?.XX.T., where?.X.?represents a rectangular matrix of?.N.?rows and?.L.?columns and?.X.T.?represents the transverse matrix of?.X.. Because?.C.?is symmetric, namely,?.C?.=?.C.T., it can be converted to a diagonal matrix of eigenvalues by a similarity transformation?.SCS.-1.?=?.SCS.T.?using an orthogonal matrix?.S.. When?.N.?is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation).. . Then the RMT-PCA applied to high-f
出版日期Book 2023
關(guān)鍵詞Big Data Analysis; RMT-PCA; Trendy Sectors of the Stock Market; RMT-Test; Evaluation of Random Number Ge
版次1
doihttps://doi.org/10.1007/978-981-19-3967-9
isbn_softcover978-981-19-3969-3
isbn_ebook978-981-19-3967-9Series ISSN 2198-4204 Series E-ISSN 2198-4212
issn_series 2198-4204
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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