Last edited by Sajind
Thursday, May 14, 2020 | History

6 edition of Applied multivariate statistical analysis found in the catalog.

Applied multivariate statistical analysis

by Wolfgang Härdle

  • 264 Want to read
  • 19 Currently reading

Published by Springer in Heidelberg, New York .
Written in English

    Subjects:
  • Multivariate analysis

  • Edition Notes

    Includes bibliographical references (p. 509-512) and index.

    StatementWolfgang Karl Härdle, Léopold Simar
    ContributionsSimar, Léopold
    Classifications
    LC ClassificationsQA278 .H346 2012
    The Physical Object
    Paginationxvii, 516 p. :
    Number of Pages516
    ID Numbers
    Open LibraryOL25306907M
    ISBN 109783642172281, 9783642172298
    LC Control Number2011944029

    Applied Multivariate Statistical Analysis (5th ed. ) 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 this new edition, the book has been updated. Get this from a library! Applied multivariate statistical analysis. [Richard A Johnson; Dean W Wichern] -- This book is concerned with statistical methods for describing and analyzing multivariate data. The authors hope that their discussions will meet the needs of experimental scientists, in a wide.

      Multivariate analysis is what people called many machine learning techniques before calling it machine learning became so lucrative. Traditional multivariate analysis emphasizes theory concerning the multivariate normal distribution, techniques based on the multivariate normal distribution, and techniques that don't require a distributional assumption, but had better work well for the.   This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major chapter revisions as well as new sections on neural networks and random effects models.

    Applied Multivariate Statistical Analysis. The Plausibility of m0 as a Value for a Normal Population Mean. Hotelling's T 2 and Likelihood Ratio Tests. Confidence Regions and Simultaneous Comparisons of Component Means. Throughout the book, the computer is used as an adjunct to the presentation of a multivariate statistical method in an empirically oriented approach. Basically, the model adopted in this book is to first present the theory of a multivariate statistical method along with the basic mathematical computations necessary for the analysis of data.


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Applied multivariate statistical analysis by Wolfgang Härdle Download PDF EPUB FB2

The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features: A new chapter on Variable Selection (Lasso, SCAD and Elastic Net) All exercises are supplemented by R and MATLAB code that can be found on The third model of this book on Applied Multivariate Statistical Analysis presents the subsequent new featuresA new Chapter on Regression Fashions has been addedAll numerical examples have been redone, updated and made reproducible in MATLAB or R, see for a.

Applied Multivariate Statistical Analysis Paperback – Ma by Wichern Johnson (Author) out of 5 stars 35 ratings. See all formats and editions Hide Cited by: The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half.

The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16)Cited by: The approach to multivariate meta-analysis presented here can be applied regardless of the form of the effect of interest.

In general, the goals of a multivariate meta-analysis are the same as those of univariate syntheses: to estimate magnitudes of effect across studies, and to examine variation in. All chapters include practical exercises that highlight applications in different multivariate data analysis fields.

All of the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features.

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NEW TO THIS EDITION: Extensively updated and rewritten chapters on confirmatory factor analysis, structural equation modeling, and model invariance improve accessibility and offer more complete examples.; A new chapter on survival analysis enhances the scope of the book.; Reorganized content for a more logical flow includes correlation and regression appearing immediately after data screening.

The fourth edition of this book on Applied Multivariate Statistical Analysis offers a new sub-chapter on Variable Selection by using least absolute shrinkage and selection operator (LASSO) and its general form the so-called Elastic Net.

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