Local Regression and Likelihood

Catherine Loader

ISBN 10: 0387987754 / ISBN 13: 9780387987750

Verlag: Springer New York, Springer US Jul 1999, 1999

Beschreibung

Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 308 pp. Englisch.

Bestandsnummer des Verkäufers 9780387987750

Bibliografische Details

• Titel: Local Regression and Likelihood
• Verlag: Springer New York, Springer US Jul 1999
• Erscheinungsjahr: 1999
• Sprache: Englisch
• ISBN-10: 0387987754
• ISBN-13: 9780387987750
• Einband: Buch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

The Origins of Local Regression.- Local Regression Methods.- Fitting with LOCFIT.- Local Likelihood Estimation.- Density Estimation.- Flexible Local Regression.- Survival and Failure Time Analysis.- Discrimination and Classification.- Variance Estimation and Goodness of Fit.- Bandwidth Selection.- Adaptive Parameter Choice.- Computational Methods.- Optimizing Local Regression.

Reseña del editor

Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, with extensions to local likelihood and density estimation. Practical information is also included on how to implement these methods in the programs S-PLUS and LOCFIT.