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Nonparametric function estimation, modeling, and simulation / James R. Thompson and Richard A. Tapia.

By: Contributor(s): Material type: TextTextPublication details: Philadelphia : Society for Industrial and Applied Mathematics, c1990.Description: xvi, 304 p. : ill. ; 23 cmISBN:
  • 9780898712612
Subject(s): DDC classification:
  • 000SA.09 23 T473
Contents:
Chapter 1. Historical background-- Chapter 2. Approaches to nonparametric density estimation-- Chapter 3. Maximum likelihood density estimation-- Chapter 4. Maximum penalized likelihood density estimation-- Chapter 5. Discrete maximum penalized likelihood density estimation-- Chapter 6. Nonparametric density estimation in higher dimensions-- Chapter 7. Nonparametric regression and intensity function estimation-- Chapter 8. Model building: speculative data analysis-- Appendix I-- Appendix II-- Appendix III-- Appendix IV-- Index.
Summary: Topics emphasized in this book include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions.
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Includes bibliographical references and index.

Chapter 1. Historical background--
Chapter 2. Approaches to nonparametric density estimation--
Chapter 3. Maximum likelihood density estimation--
Chapter 4. Maximum penalized likelihood density estimation--
Chapter 5. Discrete maximum penalized likelihood density estimation--
Chapter 6. Nonparametric density estimation in higher dimensions--
Chapter 7. Nonparametric regression and intensity function estimation--
Chapter 8. Model building: speculative data analysis--
Appendix I--
Appendix II--
Appendix III--
Appendix IV--
Index.

Topics emphasized in this book include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions.

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