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Titlebook: Applied Multivariate Statistical Analysis; Wolfgang Karl Härdle,Léopold Simar Textbook 20195th edition Springer Nature Switzerland AG 2019

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期刊全称Applied Multivariate Statistical Analysis
影响因子2023Wolfgang Karl Härdle,Léopold Simar
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发行地址Presents multivariate statistical analysis in a comprehensive way, including the most useful approaches to multi-dimensional data.Features numerous examples and exercises, including real-world applica
图书封面Titlebook: Applied Multivariate Statistical Analysis;  Wolfgang Karl Härdle,Léopold Simar Textbook 20195th edition Springer Nature Switzerland AG 2019
影响因子.This textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields, and all the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis..For this new edition, the book has been updated and extensively revised and now includes an extended chapter on cluster analysis. All solutions to the exercises are supplemented by R and MATLAB or SAS computer code and can be downloaded from the Quantlet platform. Practical exercises from this book and their solutions can also be found in the accompanying Springer book by W.K. Härdle and Z. Hlávka: .Multivariate Statistics - Exercises and Solutions...The Quantlet platform, quantlet.de, quantlet.com, quantlet.org, is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding data-driven document-based vis
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Aspektorientierte Programmierung (AOP),on the fact that it has many appealing properties: it is stable under linear transforms, zero correlation corresponds to independence, the marginals and all the conditionals are also multivariate normal variates, etc. The mathematical properties of the multinormal make analyses much simpler.
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Datenverkehr zwischen Streamhandlerntion for the response variable, . is the data matrix of the . explanatory variables and . are the errors. Linear models are not restricted to handle only linear relationships between . and .. Curvature is allowed by including appropriate higher order terms in the . matrix ..
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Theory of the Multinormalon the fact that it has many appealing properties: it is stable under linear transforms, zero correlation corresponds to independence, the marginals and all the conditionals are also multivariate normal variates, etc. The mathematical properties of the multinormal make analyses much simpler.
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Variable Selectionhen the true underlying model has a sparse representation (many parameters close to zero). The identification of relevant variables will reduce the noise and therefore improve the prediction performance of the fitted model.
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