Local Regression and Likelihood

Local Regression and Likelihood

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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...

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Bibliographic Details
Main Author: Loader, Clive (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York, 1999.
Series:Statistics and Computing,
Subjects:
Mathematics.
Economics, Mathematical.
Probabilities.
Statistics.
Probability Theory and Stochastic Processes.
Statistics and Computing/Statistics Programs.
Statistics for Business/Economics/Mathematical Finance/Insurance.
Quantitative Finance.
Online Access:Full Text via HEAL-Link
Description
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. 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.
Physical Description:XIV, 290 p. online resource.
ISBN:9780387227320
ISSN:1431-8784

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