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A User's Guide to Principal Components

2005-01-21 Mathematics
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Release : 2005-01-21
Genre : Mathematics
Kind : eBook
Book Rating : 323/5 ( reviews)

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Book Synopsis A User's Guide to Principal Components by : J. Edward Jackson

Download or read book A User's Guide to Principal Components written by J. Edward Jackson. This book was released on 2005-01-21. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of A User’s Guide to Principal Components "The book is aptly and correctly named–A User’s Guide. It is the kind of book that a user at any level, novice or skilled practitioner, would want to have at hand for autotutorial, for refresher, or as a general-purpose guide through the maze of modern PCA." –Technometrics "I recommend A User’s Guide to Principal Components to anyone who is running multivariate analyses, or who contemplates performing such analyses. Those who write their own software will find the book helpful in designing better programs. Those who use off-the-shelf software will find it invaluable in interpreting the results." –Mathematical Geology

A User's Guide to Principal Components

2005
Download A User's Guide to Principal Components PDF Online Free

Author :
Release : 2005
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis A User's Guide to Principal Components by :

Download or read book A User's Guide to Principal Components written by . This book was released on 2005. Available in PDF, EPUB and Kindle. Book excerpt: Don't get bogged down in theoretical matters and computational techniques. Focus instead on practical aspects of data reduction and interpretation. Dealing with the "how-to-do-it" as well as the '"why-it-works," this paperback edition of a Wiley bestseller is designed for practitioners of principal component analysis. Among the topics explored are extension to p variables, scaling input data, inferential procedures, operations with group data, and vector interpretation.

User's Guide to Principal Components

19??
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Release : 19??
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis User's Guide to Principal Components by : J. Edward Jackson

Download or read book User's Guide to Principal Components written by J. Edward Jackson. This book was released on 19??. Available in PDF, EPUB and Kindle. Book excerpt:

Beginner's Guide to Principal Components

2020-11-11 Mathematics
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Release : 2020-11-11
Genre : Mathematics
Kind : eBook
Book Rating : 625/5 ( reviews)

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Book Synopsis Beginner's Guide to Principal Components by : Kilem Li Gwet

Download or read book Beginner's Guide to Principal Components written by Kilem Li Gwet. This book was released on 2020-11-11. Available in PDF, EPUB and Kindle. Book excerpt: The Beginner's Guide to Principal Components is a book that introduces beginner readers to the field of principal component analysis. Principal component analysis was invented in the beginning of the twentieth century and has been extensively used by statisticians and social scientists. It has found new applications in the era of big data and artificial intelligence. With a growing number of users of principal component analysis, comes the need to present the materials for a broader audience with limited mathematical background, but with a clear desire to understand how the techniques work. This book does not require a strong background in linear algebra. All concepts related to linear or matrix algebra and needed to understand the principal components will be introduce at a basic level. However, any prior exposure to linear or matrix algebra will be helpful. The more you want to understand principal components, the deeper you need to delve into the underlying mathematics. - One can use any of the software products that implement principal component analysis, without having to worry about the underlying mathematics. However, I advise that you develop some understanding of the logic and the mechanics of principal component analysis before you start crunching numbers. - This book introduces the Excel template pca.xlsm, which can be downloaded for free at https: //agreestat.com/books/pca/pca.xlsm. I expect Excel users to find it useful for implementing the different techniques discussed in this book. Non Excel users have a few free alternative options such as the R software.

Principal Component Analysis

2013-03-09 Mathematics
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Release : 2013-03-09
Genre : Mathematics
Kind : eBook
Book Rating : 043/5 ( reviews)

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Book Synopsis Principal Component Analysis by : I.T. Jolliffe

Download or read book Principal Component Analysis written by I.T. Jolliffe. This book was released on 2013-03-09. Available in PDF, EPUB and Kindle. Book excerpt: Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.

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