Measurement, Regression, and Calibration (Oxford Statistical Science Series)

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9780198522454: Measurement, Regression, and Calibration (Oxford Statistical Science Series)

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.

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"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


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Book Description Oxford University Press, United Kingdom, 1994. Hardback. Book Condition: New. New.. Language: English . Brand New Book ***** Print on Demand *****. 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 flexible analysis of a wide range of multivariate regression problems. The last chapter presents some Bayesian approaches to pattern recognition. For teaching purposes instructors may find particular 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. Bookseller Inventory # APC9780198522454

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Book Description Oxford University Press, United Kingdom, 1994. Hardback. Book Condition: New. New.. Language: English . Brand New Book ***** Print on Demand *****.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 flexible analysis of a wide range of multivariate regression problems. The last chapter presents some Bayesian approaches to pattern recognition. For teaching purposes instructors may find particular 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. Bookseller Inventory # APC9780198522454

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Book Description OUP Oxford. Hardcover. Book Condition: New. Hardcover. 216 pages. Dimensions: 9.1in. x 5.9in. x 0.8in.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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Hardcover. Bookseller Inventory # 9780198522454

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