Loader C. Local Regression and Likelihood

Springer – 1999, 303 pages
ISBN: 0387987754, 9780387987750Separation 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.Introduction.- Univariate Local Regression.- Multivariate Local Regression.- Local Likelihood Estimation.- Density Estimation.- LOCFIT: Some additional methods Survival and Failure Time Analysis.- Discrimination and Classification.- Goodness of Fit.- Bandwidth Selection.- Adaptive Parameter Choice.- Computational Methods.- Asymptotic Theory.