Nonparametric Smoothing and Lack-of-Fit Tests (Springer Series in Statistics)

Jeffrey D. Hart

ISBN 10: 0387949801 / ISBN 13: 9780387949802

Editore: Springer, 1997

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Dati bibliografici

• Titolo: Nonparametric Smoothing and Lack-of-Fit Tests (Springer Series in Statistics)
• Editore: Springer
• Data di pubblicazione: 1997
• Lingua: Inglese
• ISBN 10: 0387949801
• ISBN 13: 9780387949802
• Rilegatura: Rilegato
• Condizione: New

Descrizione articolo

Riassunto

The The primary primary aim aim of of this this book book is is to to explore explore the the use use of of nonparametric nonparametric regres­ regres­ sion sion (i. e. , (i. e. , smoothing) smoothing) methodology methodology in in testing testing the the fit fit of of parametric parametric regression regression models. models. It It is is anticipated anticipated that that the the book book will will be be of of interest interest to to an an audience audience of of graduate graduate students, students, researchers researchers and and practitioners practitioners who who study study or or use use smooth­ smooth­ ing ing methodology. methodology. Chapters Chapters 2-4 2-4 serve serve as as a a general general introduction introduction to to smoothing smoothing in in the the case case of of a a single single design design variable. variable. The The emphasis emphasis in in these these chapters chapters is is on on estimation estimation of of regression regression curves, curves, with with hardly hardly any any mention mention of of the the lack-of­ lack-of­ fit fit problem. problem. As As such, such, Chapters Chapters 2-4 2-4 could could be be used used as as the the foundation foundation of of a a graduate graduate level level statistics statistics course course on on nonparametric nonparametric regression. regression.

Contenuti

1. Introduction.- 2. Some Basic Ideas of Smoothing.- 3. Statistical Properties of Smoothers.- 4. Data-Driven Choice of Smoothing Parameters.- 5. Classical Lack-of-Fit Tests.- 6. Lack-of-Fit Tests Based on Linear Smoothers.- 7. Testing for Association via Automated Order Selection.- 8. Data-Driven Lack-of-Fit Tests for General Parametric Models.- 9. Extending the Scope of Application.- 10. Some Examples.- A.2. Bounds for the Distribution of Tcusum.- References.