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Semiparametric Regression

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Synopses & Reviews

Publisher Comments:

Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.

Synopsis:

Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software.

Synopsis:

Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression aims to make sense of such data. Application areas include engineering, finance, medicine and public health. Semiparametric Regression explains this topic in a concise and modular fashion. The book is pitched towards researchers and professionals with little background in regression and statistically oriented scientists, such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models.

Synopsis:

This user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.

Table of Contents

1. Introduction; 2. Parametric regression; 3. Scatterplot smoothing; 4. Mixed models; 5. Automatic scatterplot smoothing; 6. Inference; 7. Simple semiparametric models; 8. Additive models; 9. Semiparametric mixed models; 10. Generalized parametric regression; 11. Generalized additive models; 12. Interaction models; 13. Bivariate smoothing; 14. Variance function estimation; 15. Measurement error; 16. Bayesian semiparametric regression; 17. Spatially adaptive splines; 18. Analyses of case studies; 19. Epilogue; A. Matrix and linear algebra; B. Vector differential equations; C. Useful results from probability theory; D. Theory for penalized splines; E. Computational issues.

Product Details

ISBN:
9780521780506
Author:
Ruppert, D.
Publisher:
Cambridge University Press
Author:
Ross, S.
Author:
Wand, M. P.
Author:
Gill, R.
Author:
Carroll, R. J.
Author:
Stein, M.
Author:
Ruppert, David
Author:
Ripley, B. D.
Author:
Williams, D.
Location:
Cambridge
Subject:
Statistics
Subject:
Regression analysis
Subject:
Nonparametric statistics
Subject:
Probability & Statistics - General
Subject:
Mathematics | Probability and Statistics
Edition Number:
1
Edition Description:
Paperback
Series:
Cambridge Series in Statistical and Probabilistic Mathematics
Series Volume:
12
Publication Date:
20030731
Binding:
HARDCOVER
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
80 line diagrams 2 colour plates
Pages:
402

Related Subjects

History and Social Science » Politics » United States » Foreign Policy
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Semiparametric Regression New Hardcover
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$155.50 In Stock
Product details 402 pages Cambridge University Press - English 9780521780506 Reviews:
"Synopsis" by , Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software.
"Synopsis" by , Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression aims to make sense of such data. Application areas include engineering, finance, medicine and public health. Semiparametric Regression explains this topic in a concise and modular fashion. The book is pitched towards researchers and professionals with little background in regression and statistically oriented scientists, such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models.
"Synopsis" by , This user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.
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