With many real-world examples, this book shows how to apply the powerful methods of smoothing splines in practice. It covers basic smoothing spline models as well as more advanced models, such as spline smoothing with correlated random errors. It also presents methods for model selection and inference. The author makes the advanced smoothing spline methodology based on reproducing kernel Hilbert space (RKHS) accessible to practitioners and students by keeping theory to a minimum. R is used throughout to implement the ...
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With many real-world examples, this book shows how to apply the powerful methods of smoothing splines in practice. It covers basic smoothing spline models as well as more advanced models, such as spline smoothing with correlated random errors. It also presents methods for model selection and inference. The author makes the advanced smoothing spline methodology based on reproducing kernel Hilbert space (RKHS) accessible to practitioners and students by keeping theory to a minimum. R is used throughout to implement the methods, with code available for download on the book's web page.
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New. Print on demand Sewn binding. Cloth over boards. 394 p. Contains: Unspecified, Illustrations, black & white, Tables, black & white, Diagrams, Figures. Chapman & Hall/CRC Monographs on Statistics and Applied Prob.
