Local Regression and Likelihood by Catherine Loader

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Summary

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.

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Local Regression and Likelihood by Catherine Loader

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.
SKU Unavailable
ISBN 13 9781475772586
ISBN 10 1475772580
Title Local Regression and Likelihood
Author Catherine Loader
Series Statistics And Computing
Condition Unavailable
Binding Type Paperback
Publisher Springer-Verlag New York Inc.
Year published 2013-09-11
Number of pages 290
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.