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Local regression and likelihood /

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Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to...

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Bibliographic Details
Main Author: Loader, Clive
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York : Springer, 1999.
Series:Statistics and computing.
Subjects:
Regression analysis.
Estimation theory.
Analyse de régression.
Estimation, Théorie de l'
MATHEMATICS > Probability & Statistics > Regression Analysis.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.
Item Description:Electronic resource.
Physical Description:1 online resource (xiii, 290 pages) : illustrations.
Bibliography:Includes bibliographical references and index.
ISBN:0387227326 (electronic bk.)
9780387227320 (electronic bk.)