Nonparametric Regression and Generalized Linear Models: A roughness penalty approach: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Autor P.J. Green, Bernard. W. Silvermanen Limba Engleză Hardback – mai 1993
The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus.
This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.
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Specificații
ISBN-13: 9780412300400
ISBN-10: 0412300400
Pagini: 194
Ilustrații: black & white illustrations
Dimensiuni: 152 x 229 x 16 mm
Greutate: 0.5 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Locul publicării:Boca Raton, United States
ISBN-10: 0412300400
Pagini: 194
Ilustrații: black & white illustrations
Dimensiuni: 152 x 229 x 16 mm
Greutate: 0.5 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Locul publicării:Boca Raton, United States
Public țintă
Professional and Professional Practice & DevelopmentRecenzii
"...provides an excellent introduction."
- Short Book Reviews of the ISI
"It is well written and very reliable."
- Technometrics
- Short Book Reviews of the ISI
"It is well written and very reliable."
- Technometrics
Cuprins
Preface. Introduction. Approaches to Regression. Roughness Penalties. Extensions of the Roughness Penalty Approach. Computing the Estimates. Further Reading. Interpolating and Smoothing Splines. One-Dimensional Case: Further Topics. Partial Splines. Generalized Linear Models. Extending the Model. Thin Plate Splines. Available Software. Reference. Author Index. Subject Index.
Notă biografică
P.J. Green, Bristol Univesity. Bernard. W. Silverman St. Peters College, Oxford.
Descriere
Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique provides a unifying approach to a wide range of smoothing problems. The emphasis is methodological rather than theoretical, and the authors concentrate on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students.