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"This book provides an overview of the theory, methods, and application of local regression and likelihood. The first five chapters introduce the problems, first in the local regression setting, followed by extensions to likelihood-based regression models and density estimation. The remaining chapters cover a range of advanced topics and applications, including robust smoothing, survival analysis, classification, and model selection issues."--BOOK JACKET.
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Edition Notes
Includes bibliographical references and index.
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Feedback?July 17, 2024 | Edited by MARC Bot | import existing book |
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