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Nonparametric Smoothing and Lack-of-Fit Tests

Nonparametric Smoothing and Lack-of-Fit Tests

Jeffrey Hart

133,86 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2012
Materia
Probabilidad y estadística
ISBN:
9781475727241
133,86 €
IVA incluido
Disponible

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Sobre IBD

An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods, addressing both applied and theoretical aspects of the model checking problems. As such, the book is of interest to practitioners of statistics and researchers investigating either lack-of-fit tests or nonparametric smoothing ideas. The first four chapters introduce the problem of estimating regression functions by nonparametric smoothers, primarily those of kernel and Fourier series type, and could be used as the foundation for a graduate level course on nonparametric function estimation. The prerequisites for a full appreciation of the book are a modest knowledge of calculus and some familiarity with the basics of mathematical statistics.

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Otros libros del autor

  • Nonparametric Smoothing and Lack-of-Fit Tests
    Jeffrey Hart
    An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods, addressing both applied and theoretical aspects of the model checking problems. As such, the book is of interest to practitioners of statisti...