P J Brown

Measurement, Regression, and Calibration

• Gebundenes Buch

Produktbeschreibung

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.

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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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Produktdetails

• Verlag: Hurst & Co.
• Seitenzahl: 210
• Erscheinungstermin: 21. Juli 1994
• Englisch
• Abmessung: 229mm x 152mm x 16mm
• Gewicht: 481g
• ISBN-13: 9780198522454
• ISBN-10: 0198522452
• Artikelnr.: 21923207

Inhaltsangabe

Introduction
1: Simple linear regression
2: Multiple regression and calibration
3: Regularized multiple regression
4: Multivariate calibration
5: Regession on curves
6: Non-linearity and selection
7: Pattern recognition
A: Distribution theory
B: Conditional inference
C: Regularization dominance
E: Partial least-squares algorithm
Bibliography
Index