Applied Multivariate Statistical Analysis
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Applied Multivariate Statistical Analysis
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer Nature
Release Date : 2024-09-28
Applied Multivariate Statistical Analysis written by Wolfgang Karl Härdle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-28 with Mathematics categories.
Now in its sixth edition, this textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. Each chapter features hands-on exercises that showcase applications across various fields of multivariate data analysis. These exercises utilize high-dimensional to ultra-high-dimensional data, reflecting real-world challenges in big data analysis. For this new edition, the book has been updated and revised and now includes new chapters on modern machine learning techniques for dimension reduction and data visualization, namely locally linear embedding, t-distributed stochastic neighborhood embedding, and uniform manifold approximation and projection, which overcome the shortcomings of traditional visualization and dimension reduction techniques. Solutions to the book’s exercises are supplemented by R and MATLAB or SAS computer code and are available online on the Quantlet and Quantinar platforms. 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.
Applied Multivariate Statistical Analysis
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2015-02-26
Applied Multivariate Statistical Analysis written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with Business & Economics categories.
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. 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: 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 www.quantlet.de. The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.
Applied Multivariate Statistical Analysis
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Author : Richard Arnold Johnson
language : en
Publisher:
Release Date : 2002
Applied Multivariate Statistical Analysis written by Richard Arnold Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.
& This market leader offers a readable introduction to the statistical analysis of multivariate observations. Gives readers the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Starts with a formulation of the population models, delineates the corresponding sample results, and liberally illustrates everything with examples. & Offers an abundance of examples and exercises based on real data.& Appropriate for experimental scientists in a variety of disciplines.
Applied Multivariate Statistical Analysis
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Applied Multivariate Statistical Analysis written by Wolfgang Karl Härdle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Most of the observable phenomena in the empirical sciences are of multivariate nature. This book presents the tools and concepts of multivariate data analysis with a strong focus on applications. The text is devided into three parts. The first part is devoted to graphical techniques describing the distributions of the involved variables. The second part deals with multivariate random variables and presents from a theoretical point of view distributions, estimators and tests for various practical situations. The last part covers multivariate techniques and introduces the reader into the wide basket of tools for multivariate data analysis. The text presents a wide range of examples and 228 exercises.
Applied Multivariate Data Analysis
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Author : Brian S. Everitt
language : en
Publisher: Wiley
Release Date : 2009-04-20
Applied Multivariate Data Analysis written by Brian S. Everitt and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-20 with Mathematics categories.
Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. 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 for longitudinal data. Maintaining the easy-going style of the first edition, the authors provide clear explanations of each technique, as well as supporting figures and examples, and minimal technical jargon. With extensive exercises following every chapter, 'Applied Multivariate Data Analysis' is a valuable resource for students on applied statistics courses and applied researchers in many disciplines.
Applied Multivariate Statistical Analysis
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Author : Richard Arnold Johnson
language : en
Publisher: Prentice Hall
Release Date : 2007
Applied Multivariate Statistical Analysis written by Richard Arnold Johnson and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Multivariate analysis categories.
This market leader offers a readable introduction to the statistical analysis of multivariate observations. Gives readers the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Starts with a formulation of the population models, delineates the corresponding sample results, and liberally illustrates everything with examples. Offers an abundance of examples and exercises based on real data. Appropriate for experimental scientists in a variety of disciplines.
Topics In Applied Multivariate Analysis
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Author : D. M. Hawkins
language : en
Publisher: Cambridge University Press
Release Date : 1982-04-22
Topics In Applied Multivariate Analysis written by D. M. Hawkins and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-04-22 with Mathematics categories.
Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.
Applied Multivariate Statistical Analysis
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Author : Wolfgang Karl Hardle
language : en
Publisher:
Release Date : 2014-01-15
Applied Multivariate Statistical Analysis written by Wolfgang Karl Hardle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Applied Multivariate Statistical Analysis
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Author : Richard Arnold Johnson
language : en
Publisher:
Release Date : 1992
Applied Multivariate Statistical Analysis written by Richard Arnold Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.
Explores the statistical methods for describing and analyzing multivariate data. It's goal is to provide readers with the knowledge necessary to make proper interpretations, and select appropriate techniques for analyzing multivariate data Coverage includes: Detecting Outliers and Data Cleaning; Multivariate Quality Control; Monitoring Quality with Principal Components; and Correspondence Analysis, Biplots, and Procrustes Analysis.
An Introduction To Applied Multivariate Analysis With R
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Author : Brian Everitt
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-23
An Introduction To Applied Multivariate Analysis With R written by Brian Everitt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-23 with Mathematics categories.
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.