Identifying Rank-Influential Groups of Observations in Linear Regression

Language: English

Published by Forgotten Books, 2018

1332264611 / 9781332264612

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Print on Demand. This book explores the identification of groups of observations that exert a strong influence on the results of linear regression modeling. The author presents mathematical characterizations of these groups and proposes methods using factor-analytic rotation algorithms and projection pursuit techniques. One method focuses on finding directions in which many cases are extreme inliers, while the other examines directions in which most cases are outlying. Both methods avoid a combinatorial search through possible subsets of cases, making them computationally feasible for data sets of various sizes. The author provides examples to illustrate how the methods perform, and the book concludes with a discussion of related diagnostic methods. The insights provided by this book are significant for researchers and practitioners who use linear regression modeling to analyze data, as they highlight the importance of considering the impact of influential groups of observations on the reliability and validity of their results. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.…

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Title
Identifying Rank-Influential Groups of Observations in Linear Regression
Author
Peter J. Kempthorne
Publisher
Forgotten Books
Publication year
2018
Condition
New
Book Type
print-on-demand item
Binding
Paperback
Language
English
ISBN 10
1332264611
ISBN 13
9781332264612
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Forgotten Books

London, United Kingdom

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Forgotten Books’ Classic Reprint Series utilizes the latest technology to regenerate facsimiles of historically important writings. Careful attention has been made to accurately preserve the original format of each page whilst digitally enhancing the quality of the aged text.

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