Paul H. C. Eilers is Professor Emeritus of Genetical Statistics at the Erasmus University Medical Center Rotterdam. He received his Ph.D. in biostatistics. His research interests include high-throughput genomic data analysis, chemometrics, smoothing, longitudinal data analysis, survival analysis, and statistical computing. He has published extensively on these subjects. Brian D. Marx is Professor in the Department of Experimental Statistics at Louisiana State University. He received his Ph.D. in statistics. His main research interests include smoothing, ill-conditioned regression problems, and high-dimensional chemometric applications, and he has numerous publications on these topics. He is currently serving as coordinating editor for the journal Statistical Modelling. He is coauthor of two books and is a Fellow of the American Statistical Association.

• 1. Introduction; 2. Bases, penalties, and likelihoods; 3. Optimal smoothing in action; 4. Multidimensional smoothing; 5. Smoothing of scale and shape; 6. Complex counts and composite links; 7. Signal regression; 8. Special subjects; A. P-splines for the impatient; B. P-splines and competitors; C. Computational details; D. Array algorithms; E. Mixed model equations; F. Standard errors in detail; G. The website.

'The title says it all. This is a practical book which shows how P-splines are used in an astonishingly wide range of settings. If you use P-splines already the book is indispensable; if you don't, then reading it will convince you it's time to start. Every example comes with an R-program available on the book's web-site, an important feature for the experienced user and novice alike.' Iain Currie, Heriot-Watt University