http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (xiii, 290 pages) : illustrations.
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.
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.
Includes bibliographical references and index.