Smoothing and regression. Approaches computation and application - Michael G. Schimek

Michael G. Schimek

ISBN 10: 0471179469 / ISBN 13: 9780471179467

Published by 2000, 2000

About this Item

Occasion - Bon Etat - Smoothing and regression. Approaches computation and application (2000) - Grand Format.

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Bibliographic Details

• Title: Smoothing and regression. Approaches computation and application - Michael G. Schimek
• Publisher: 2000
• Publication Date: 2000
• Language: English
• ISBN 10: 0471179469
• ISBN 13: 9780471179467
• Binding: Hardcover
• Condition: Used: Good
• Seller catalogs:
  • Grand Format
  • Grand Format Pages: Mathématiques

About this title

Synopsis

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.

About the Author

MICHAEL G. SCHIMEK, PhD, DPhil, is Professor of Statistics and Biometrics in the Department of Medical Informatics, Statistics, and Documentation at Karl-Franzens-University of Graz, Austria, and Adjunct Professor of Methodology in the Department of Psychology at the University of Vienna, Austria.