Product Description

Volume 43 of the series entitled, Monographs on Statistics and Applied Probability. Describes a new array of power tools for data analysis, based on nonparametric regression or smoothing techniques.

Product Details

• Amazon Sales Rank: #395413 in Books
• Published on: 1990-06-01
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 352 pages

Review
That the authors succeed in conveying their message is largely due to the extremely clear and effective organization of the text. General concepts are introduced, illustrated with relatively simple applications, and then re-examined at a more theoretical level.
-Journal of the Royal Statistical Society, Series C
This book aims to 'provide an up-to-date survey of current research in additive modelling,' with the 'emphasis on practical rather than theoretical.' With that in mind, the book does extremely well.
-Statistics in Medicine
Generalized Additive Models is a good starting point for researchers wishing to initiate themselves in the vast and burgeoning area of large-sample nonparametric model fitting.
-Journal of the American Statistical Association
Overall, my impressions of this book are very favorable, and I consider it a book worth owning... The material is presented clearly and attractively. I recommend it to anyone interested in or needing to use extensions to the general linear model.
-Technometrics
... a complete introduction to the topic in a single monograph... a very readable book that provides the reader with great insight into a vast array of data analysis techniques... an excellent text for a course on smoothing-based analysis techniques... highly recommended to any reader interested in an introduction to many of the recent developments in data analysis.
-Siam Review

That the authors succeed in conveying their message is largely due to the extremely clear and effective organization of the text. General concepts are introduced, illustrated with relatively simple applications, and then re-examined at a more theoretical level.
-Journal of the Royal Statistical Society, Series C
This book aims to provide an up-to-date survey of current research in additive modelling, with the emphasis on practical rather than theoretical. With that in mind, the book does extremely well.
-Statistics in Medicine
Generalized Additive Models is a good starting point for researchers wishing to initiate themselves in the vast and burgeoning area of large-sample nonparametric model fitting.
-Journal of the American Statistical Association
Overall, my impressions of this book are very favorable, and I consider it a book worth owning... The material is presented clearly and attractively. I recommend it to anyone interested in or needing to use extensions to the general linear model.
-Technometrics
... a complete introduction to the topic in a single monograph... a very readable book that provides the reader with great insight into a vast array of data analysis techniques... an excellent text for a course on smoothing-based analysis techniques... highly recommended to any reader interested in an introduction to many of the recent developments in data analysis.
-Siam Review

Customer Reviews

nice generalization of linear models
Believe it or not this important topic in applied statistics was developed by Hastie and Tibshirani when they were graduate students, a sure sign of greatness to come. After their graduation this highly acclaimed book came out explaining both the theory and pratice of generalized additive models in a clear and concise way. Generalized additive models are similar to generalized linear models in their additive structure but the form of the additive functions is much more general.
Both Hastie and Tibshirani are now Stanford professors in the Statistics Department and both have written other excellent books including their joint publication with Jerry Friedman "The Elements of Statistical Learning" and Tibshirani along with Efron wrote an excellent monograph on bootstrap.

A complex topic made readable.
A medical doctor recommended that I (a statistician) use generalized additive models on a project that he was involved with. We were pleased with the results of the modelling as they gave us some new insights on his topic and it was very rewarding

Because we were so impressed with the results, we both took the above book out of the library to read. I started the book with some trepidation as I feared it was going to be a complex topic and in some respects I was right. However, right from the encouraging quotes in the preface and into the text itself, I felt the authors were making a great effort to make the book readable.

The medico found that the explanations and examples were well written. His comment was that even a non-statistician could grasp what was going on but that there was enough theory that a statistician would be happy too!

developed by Stanford graduates students
Believe it or not this important topic in applied statistics was developed by Hastie and Tibshirani when they were graduate students, a sure sign of greatness to come. After their graduation this highly acclaimed book came out explaining both the theory and pratice of generalized additive models in a clear and concise way. Generalized additive models are similar to generalized linear models in their additive structure but the form of the additive functions is much more general.

Both Hastie and Tibshirani are now Stanford professors in the Statistics Department and both have written other excellent books including their joint publication with Jerry Friedman "The Elements of Statistical Learning" and Tibshirani along with Efron wrote an excellent monograph on bootstrap.