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Titlebook: Applied Multivariate Statistical Analysis; Wolfgang H?rdle,Léopold Simar Textbook 20072nd edition Springer-Verlag Berlin Heidelberg 2007 A

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期刊全稱Applied Multivariate Statistical Analysis
影響因子2023Wolfgang H?rdle,Léopold Simar
視頻videohttp://file.papertrans.cn/160/159982/159982.mp4
發(fā)行地址Wide scope of methods and applications.Quantlets in R and Matlab available online.Many examples and exercises.Includes supplementary material:
圖書封面Titlebook: Applied Multivariate Statistical Analysis; Wolfgang H?rdle,Léopold Simar Textbook 20072nd edition Springer-Verlag Berlin Heidelberg 2007 A
影響因子.Most of the observable phenomena in the empirical sciences are of a multivariate nature.In financial studies, assets in stock markets are observed simultaneously and their joint development is analyzed to better understand general tendencies and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying theoretical structure of these and many other quantitative studies of applied sciences is multivariate. Focussing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who face statistical data analysis. .In this second edition a wider scope of methods and applications of multivariate statistical analysis is introduced. All quantlets have been translated into the R and Matlab language and are made available online..
Pindex Textbook 20072nd edition
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Hypothesis TestingIn the preceding chapter, the theoretical basis of estimation theory was presented. Now we turn our interest towards testing issues: we want to test the hypothesis . that the unknown parameter . belongs to some subspace of ?.. This subspace is called the . and will be denoted by Ω. ? ∝..
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Entwicklung und Situation des Baumarktes observations of a variable vector . in ?.. That is, we suppose that each observation . has . dimensions: . and that it is an observed value of a variable vector . ∈ ?.. Therefore, . is composed of . random variables: . where ., for . = 1, . . ., ., is a one-dimensional random variable. How do we be
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