Graphical Models In Applied Multivariate Statistics
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Graphical Models In Applied Multivariate Statistics
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Author : J. Whittaker
language : en
Publisher: John Wiley & Sons
Release Date : 1990
Graphical Models In Applied Multivariate Statistics written by J. Whittaker and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. Following the theorem-proof-remarks format, this introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with solutions are included.
Graphical Models In Applied Multivariate Statistics
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Author :
language : en
Publisher:
Release Date : 1996
Graphical Models In Applied Multivariate Statistics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
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.
Applied Multivariate Statistics With R
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Author : Daniel Zelterman
language : en
Publisher: Springer
Release Date : 2015-08-03
Applied Multivariate Statistics With R written by Daniel Zelterman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-03 with Medical categories.
This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary.
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.
A state of the art presentation of the tools and concepts of multivariate data analysis with a strong focus on applications. 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 distributions, estimators and tests for various practical situations. The last part covers mulivariate techniques and introduces the reader into the wide variety of tools for multivariate data analysis. The text presents a wide range of examples and 228 exercises.
Applied Multivariate Statistics With Sas Software
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Author : Ravindra Khattree
language : en
Publisher: Wiley-SAS
Release Date : 1999-04-09
Applied Multivariate Statistics With Sas Software written by Ravindra Khattree and has been published by Wiley-SAS this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-04-09 with Mathematics categories.
Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS® Software, Second Edition provides a unique approach to this topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information on * mixed effects models * applications of the MIXED procedure * regression diagnostics with the correspoding IML procedure code * covariance structures. The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.
An Introduction To Applied Multivariate Analysis
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Author : Tenko Raykov
language : en
Publisher: Routledge
Release Date : 2008-03-10
An Introduction To Applied Multivariate Analysis written by Tenko Raykov and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-10 with Business & Economics categories.
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe
Handbook Of Applied Multivariate Statistics And Mathematical Modeling
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Author : Howard E.A. Tinsley
language : en
Publisher: Academic Press
Release Date : 2000-05-22
Handbook Of Applied Multivariate Statistics And Mathematical Modeling written by Howard E.A. Tinsley and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-22 with Mathematics categories.
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.
Multivariate Statistics
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Author : Wolfgang Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-27
Multivariate Statistics written by Wolfgang 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 2007-07-27 with Computers categories.
The authors have cleverly used exercises and their solutions to explore the concepts of multivariate data analysis. Broken down into three sections, this book has been structured to allow students in economics and finance to work their way through a well formulated exploration of this core topic. The first part of this book is devoted to graphical techniques. The second deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The final section contains a wide variety of exercises in applied multivariate data analysis.
Applied Multivariate Data Analysis
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Author : Brian S. Everitt
language : en
Publisher: Wiley
Release Date : 2010-06-28
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 2010-06-28 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.