Items related to Measurement, Regression, and Calibration (Oxford Statistical...
Synopsis
With an abundance of helpful examples, this text expertly presents the essentials of measurement, regression, and calibration. The book develops the fundamentals and underlying theories of key techniques in a clear, step-by-step progression, starting with standard least squares prediction of a single variable and moving on to shrinkage techniques for multiple variables. Self-contained chapters discuss methods that have been specifically developed for spectroscopy, likelihood and Bayesian inference (which may be applied to a wide range of multivariate regression problems), and Bayesian approaches to pattern recognition, among other topics. Ideal for instruction as well as for reference, Measurement, Regression, and Calibration will be a valuable addition to the bookshelves of professionals and advanced students in statistics and other pertinent fields.
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About the Author
Philip J. Brown is at University of Liverpool.
Review
"Working statisticians, particularly chemometricians, will find it useful for summarizing and clarifying the choices of models and procedures available to them for inference problems that they often encounter and for which there are few alternative references. Academic statisticians will want to use this monograph as supplementary reading for graduate-level courses in regression and as a quick entry for finding open questions requiring research." -- Technometrics
"Several numerical examples with numerous figures are helpful in understanding the motivation and the theory developed here. A bibliography of selected references and appendices concerning distribution theory in multivariate analysis are also provided. The book deals with various topics which are not discussed in detail in the literature on regression models. Furthermore, the emphasis is on calibration and the Bayesian approach. Such features of the book make it a very useful reference." -- Mathematical Reviews
"Brown provides a succinct but very clear overview of 'regularized' regression. . .a valuable work for researchers and statisticians. . ." --Choice
"This book deals with sufficiently sophisticated theory and applications of regression and calibration with an extensive emphasis on controlled calibration. It is lucidly written and provides a wealth of information in the course of a mere 169 pages. The book will also be found very useful as a reference text by practitioners."--SIAM Review
"[An] outstanding job. . .in describing approaches for building less than full rank models. . .I recommend this book highly."--Journal of Quality Technology
"About this title" may belong to another edition of this title.
- PublisherClarendon Press
- Publication date1994
- ISBN 10 0198522452
- ISBN 13 9780198522454
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages210
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Measurement, Regression, and Calibration (Volume 12)
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Condition: Good. Volume 12. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9780198522454. Seller Inventory # 9878127
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Measurement, Regression, and Calibration
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Measurement, Regression, and Calibration (Oxford Statistical Science Series, 12)
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Measurement, Regression, and Calibration (Oxford Statistical Science Series)
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Measurement, Regression, and Calibration
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Measurement, Regression, and Calibration (Hardcover)
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Oxford University Press, Oxford, 1994
ISBN 10: 0198522452
ISBN 13: 9780198522454
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Hardcover. Condition: new. Hardcover. The book starts with a range of examples and develops techniques progressively, starting with standard least squares prediction of a single variable from another and moving onto shrinkage techniques for multiple variables. Chapters 6 and 7 refer mostly to methods that have been specifically developed for spectroscopy. The other chapters are quite general in their applicability. Likelihood and Bayesian inference features strongly, the latter allowing flexibleanalysis of a wide range of multivariate regression problems. The last chapter presents some Bayesian approaches to pattern recognition.For teaching purposes instructors may findparticular chapters sufficiently self contained to recommend in isolation as reference or reading material. For example chapter 4 gives an in depth development of a range of shrinkage techniques. including partial least squares regression, ridge regression and principal components regression; together with discussion of the recently proposed continuum regression. Chapter 8 on pattern recognition may also be of us by itself in courses on multivariate analysis and Bayesian Statistics. This book explains the statistical theory behind a range of regression problems in which one set of variables is predicted from another. The applications are from industry and medicine where the researchers are using sophisticated electronic measuring devices that are capable of monitoring very many variables. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780198522454
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Measurement, Regression, and Calibration: 12 (Oxford Statistical Science Series)
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Measurement, Regression, and Calibration: 12 (Oxford Statistical Science Series)
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