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Introduction to Multivariate Analysis

1981-05-15 Mathematics
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Release : 1981-05-15
Genre : Mathematics
Kind : eBook
Book Rating : 400/5 ( reviews)

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Book Synopsis Introduction to Multivariate Analysis by : Chris Chatfield

Download or read book Introduction to Multivariate Analysis written by Chris Chatfield. This book was released on 1981-05-15. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the analysis of multivariate data.It describes multivariate probability distributions, the preliminary analysisof a large -scale set of data, princ iple component and factor analysis, traditional normal theory material, as well as multidimensional scaling andcluster analysis.Introduction to Multivariate Analysis provides a reasonable blend oftheory and practice. Enough theory is given to introduce the concepts andto make the topics mathematically interesting. In addition the authors discussthe use (and misuse) of the techniques in pra ctice and present appropriatereal-life examples from a variety of areas includ ing agricultural research, soc iology and crim inology. The book should be suitable both for researchworkers and as a text for students taking a course on multivariate analysi

An Introduction to Applied Multivariate Analysis with R

2011-04-23 Mathematics
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Release : 2011-04-23
Genre : Mathematics
Kind : eBook
Book Rating : 508/5 ( reviews)

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Book Synopsis An Introduction to Applied Multivariate Analysis with R by : Brian Everitt

Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt. This book was released on 2011-04-23. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Multivariate Analysis

2014-06-06 Mathematics
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Release : 2014-06-06
Genre : Mathematics
Kind : eBook
Book Rating : 287/5 ( reviews)

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Book Synopsis Introduction to Multivariate Analysis by : Sadanori Konishi

Download or read book Introduction to Multivariate Analysis written by Sadanori Konishi. This book was released on 2014-06-06. Available in PDF, EPUB and Kindle. Book excerpt: Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It primarily focuses on regression modeling, classification and discrimination, dimension reduction, and clustering. The text thoroughly explains the concepts and derivations of the AIC, BIC, and related criteria and includes a wide range of practical examples of model selection and evaluation criteria. To estimate and evaluate models with a large number of predictor variables, the author presents regularization methods, including the L1 norm regularization that gives simultaneous model estimation and variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for researchers and practitioners in industrial and systems engineering, information science, life science, and other areas.

Introduction to Multivariate Statistical Analysis in Chemometrics

2016-04-19 Mathematics
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Release : 2016-04-19
Genre : Mathematics
Kind : eBook
Book Rating : 491/5 ( reviews)

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Book Synopsis Introduction to Multivariate Statistical Analysis in Chemometrics by : Kurt Varmuza

Download or read book Introduction to Multivariate Statistical Analysis in Chemometrics written by Kurt Varmuza. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as

An Introduction to Multivariate Statistical Analysis

2003-07-25 Business & Economics
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Release : 2003-07-25
Genre : Business & Economics
Kind : eBook
Book Rating : 919/5 ( reviews)

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Book Synopsis An Introduction to Multivariate Statistical Analysis by : T. W. Anderson

Download or read book An Introduction to Multivariate Statistical Analysis written by T. W. Anderson. This book was released on 2003-07-25. Available in PDF, EPUB and Kindle. Book excerpt: Perfected over three editions and more than forty years, this field- and classroom-tested reference: * Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. * Treats all the basic and important topics in multivariate statistics. * Adds two new chapters, along with a number of new sections. * Provides the most methodical, up-to-date information on MV statistics available.

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