Smoothing and Regression: Approaches, Computation, and Application

Smoothing and Regression: Approaches, Computation, and Application book cover

Smoothing and Regression: Approaches, Computation, and Application

Author(s): Michael G. Schimek

  • Publisher: Wiley–Blackwell
  • Publication Date: 22 Aug. 2000
  • Language: English
  • Print length: 640 pages
  • ISBN-10: 0471179469
  • ISBN-13: 9780471179467

Book Description

A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis. Using examples of applications from the biosciences, environmental sciences, engineering, and economics, as well as medical research and marketing, this volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special features of this book include: Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines A unified, easy-to-follow format Contributions from more than 25 leading researchers from around the world More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems Extensive end-of-chapter references For professionals and aspiring professionals in statistics, applied mathematics, computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.

Editorial Reviews

Review

From the publishers description: “…a unique and important new resource destined to become on of the most frequently consulted references in the field.” (Mathematical Reviews, 2001 f) “…provides a comprehensive, concise coverage of statistics for engineers and scientists. I would recommend the use of this book for teaching statistics students…” (Journal of Quality Technology, Vol. 34, No. 1, January 2002)

From the Back Cover

A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression

Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing

techniques. It introduces, describes, and in some cases compares a large number

of the latest and most advanced techniques for regression modeling. Unlike

many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis.

Using examples of applications from the biosciences, environmental sciences,

engineering, and economics, as well as medical research and marketing, this

volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special

features of this book include:

*Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines

*A unified, easy-to-follow format

*Contributions from more than 25 leading researchers from around the world

*More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems

*Extensive end-of-chapter references

For professionals and aspiring professionals in statistics, applied mathematics,

computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.

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