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Local Regression and Likelihood

  • Book
  • © 1999

Overview

Authors:
  1. Clive Loader

    1. Lucent Technologies, Murray Hill, USA

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Part of the book series: Statistics and Computing (SCO)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xiii
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  2. The Origins of Local Regression

    • Clive Loader
    Pages 1-14

  3. Local Regression Methods

    • Clive Loader
    Pages 15-44

  4. Fitting with LOCFIT

    • Clive Loader
    Pages 45-58

  5. Local Likelihood Estimation

    • Clive Loader
    Pages 59-78

  6. Density Estimation

    • Clive Loader
    Pages 79-100

  7. Flexible Local Regression

    • Clive Loader
    Pages 101-118

  8. Survival and Failure Time Analysis

    • Clive Loader
    Pages 119-137

  9. Discrimination and Classification

    • Clive Loader
    Pages 139-157

  10. Variance Estimation and Goodness of Fit

    • Clive Loader
    Pages 159-175

  11. Bandwidth Selection

    • Clive Loader
    Pages 177-194

  12. Adaptive Parameter Choice

    • Clive Loader
    Pages 195-208

  13. Computational Methods

    • Clive Loader
    Pages 209-222

  14. Optimizing Local Regression

    • Clive Loader
    Pages 223-237

  15. Back Matter

    Pages 239-290
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Keywords

About this book

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.

Authors and Affiliations

  • Lucent Technologies, Murray Hill, USA

    Clive Loader

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