Local Regression and Likelihood

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Springer New York, Jul 30, 1999 - Mathematics - 290 pages
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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.

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References to this book

Empirical Likelihood
Art B. Owen
Limited preview - 2001
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