Clive Loader

Local Regression and Likelihood (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 290
• Erscheinungstermin: 9. Mai 2006
• Englisch
• ISBN-13: 9780387227320
• Artikelnr.: 43998631

Autorenporträt

Smoothing methods play an important role in many areas of statistics. This book explains how to implement these methods in several popular statistical programs including S-PLUS.

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.