Local Regression and Likelihood

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.

List of contents

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.

Product details

• Authors: Catherine Loader, Clive Loader
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 22.04.2014
• EAN: 9781475772586
• ISBN: 978-1-4757-7258-6
• No. of pages: 290
• Dimensions: 155 mm x 16 mm x 235 mm
• Weight: 474 g
• Illustrations: XIV, 290 p.
• Series: Statistics and Computing; Statistics and Computing
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics