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Semiparametric Regression
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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 smoothing; 18. Analyses; 19. Epilogue; A. Technical complements; B. Computational issues.

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This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.

Reviews

'I would recommend this book to anyone interested in the field. it is very readable, informative without being heavy, and (excellent news) comes in a paperback version as well as hardback.' Publication of the International Statistical Institute 'I would recommend this book to anyone interested in the field. It is very readable, informative without being heavy, and (excellent news) comes in a paperback version as well as hardback.' Short Book Reviews 'This great book is the first one to remove barriers and to close gaps between advanced statistical methodology and applied research in various fields ... I highly recommend this book ... It provides a very readable access to modern semiparametric regression, demonstrates its potential in various applications, and is an inspiring source for new ideas. I enjoyed reading this book.' L. Fahrmeir, Ludwig Maximilian University Biometrics '... contains clear presentations of new developments in the field and also the state of the art in classical methods ... I found it an easily readable book; its coverage of material was extensive and well explained and well illustrated ... I found the material useful and I recommend it strongly to anyone who is interested in modern nonparametric methods, whether they are expert or not ... But here are 500-odd pages of good teaching material, nicely done, culminating in the arc-sine law and the Black-Scholes formula: anyone teaching probability would be glad to have it to hand.' The Journal of the Royal Statistical Society 'This book provides an extensive overview of techniques for semiparametric regression ... I think it may be very useful for a more practically oriented audience.' Kwantitatieve Methoden '... an easily readable book; its coverage of material was extensive and well explained and well illustrated ... I recommend it strongly to anyone who is interested in modern nonparametric methods, whether they are expert or not.' Marian Scott, University of Glasgow Journal of the Royal Statistical Society '... provides a great overview of semiparametric regression and it is a useful guide to practical semiparametric analyses using standard statistical software.' Metrika 'This book is a very nice book for data analysis and indicates how to flexibly develop and analyze complex models using penalized spline functions. The examples are nontrivial and very useful, but there are no attempts to develop an asymptotic theory.' Mathematical Reviews

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