From the publisher's description: „... a unique and important newresource destined to become on of the most frequently consultedreferences in the field.“ (Mathematical Reviews, 2001 f)
„... provides a comprehensive, concise coverage of statistics forengineers and scientists. I would recommend the use of this bookfor teaching statistics students...“ (Journal of QualityTechnology, Vol. 34, No. 1, January 2002)
Smoothing and Regression
Approaches, Computation, and Application
herausgegeben von Michael G. SchimekA comprehensive introduction to a wide variety of univariate andmultivariate smoothing techniques for regression
Smoothing and Regression: Approaches, Computation, and Applicationbridges the many gaps that exist among competing univariate andmultivariate smoothing techniques. It introduces, describes, and insome cases compares a large number of the latest and most advancedtechniques for regression modeling. Unlike many other volumes onthis topic, which are highly technical and specialized, this bookdiscusses all methods in light of both computational efficiency andtheir applicability for real data analysis.
Using examples of applications from the biosciences, environmentalsciences, engineering, and economics, as well as medical researchand marketing, this volume addresses the theory, computation, andapplication 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 ofthis book include:
* Comprehensive coverage of smoothing and regression with softwarehints and applications from a wide variety of disciplines
* A unified, easy-to-follow format
* Contributions from more than 25 leading researchers from aroundthe world
* More than 150 illustrations also covering new graphicaltechniques important for exploratory data analysis andvisualization of high-dimensional problems
* Extensive end-of-chapter references
For professionals and aspiring professionals in statistics, appliedmathematics, computer science, and econometrics, as well as forresearchers in the applied and social sciences, Smoothing andRegression is a unique and important new resource destined tobecome one the most frequently consulted references in the field.
Smoothing and Regression: Approaches, Computation, and Applicationbridges the many gaps that exist among competing univariate andmultivariate smoothing techniques. It introduces, describes, and insome cases compares a large number of the latest and most advancedtechniques for regression modeling. Unlike many other volumes onthis topic, which are highly technical and specialized, this bookdiscusses all methods in light of both computational efficiency andtheir applicability for real data analysis.
Using examples of applications from the biosciences, environmentalsciences, engineering, and economics, as well as medical researchand marketing, this volume addresses the theory, computation, andapplication 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 ofthis book include:
* Comprehensive coverage of smoothing and regression with softwarehints and applications from a wide variety of disciplines
* A unified, easy-to-follow format
* Contributions from more than 25 leading researchers from aroundthe world
* More than 150 illustrations also covering new graphicaltechniques important for exploratory data analysis andvisualization of high-dimensional problems
* Extensive end-of-chapter references
For professionals and aspiring professionals in statistics, appliedmathematics, computer science, and econometrics, as well as forresearchers in the applied and social sciences, Smoothing andRegression is a unique and important new resource destined tobecome one the most frequently consulted references in the field.
