Bayesian Methods for Nonlinear Classification and Regression, David G. T. Denison
Автор: Wakefield Название: Bayesian and Frequentist Regression Methods ISBN: 1441909249 ISBN-13(EAN): 9781441909244 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.
Автор: Vittinghoff Название: Regression Methods in Biostatistics ISBN: 0387202757 ISBN-13(EAN): 9780387202754 Издательство: Springer Рейтинг: Цена: 11313.00 р. Наличие на складе: Поставка под заказ.
Описание: An introduction to the multipredictor regression methods widely used in biostatistics. This book covers linear models for continuous outcomes; logistic models for binary outcomes; the Cox model for right-censored survival times; repeated-measures models for longitudinal and hierarchical outcomes; and linear models for counts and other outcomes.
Автор: Sanders J. A., Verhulst F., Murdock J. Название: Averaging Methods in Nonlinear Dynamical Systems ISBN: 0387489169 ISBN-13(EAN): 9780387489162 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Perturbation theory and in particular normal form theory has shown strong growth during the last decades. So it is not surprising that the authors have presented an extensive revision of the first edition of the Averaging Methods in Nonlinear Dynamical Systems book. There are many changes, corrections and updates in chapters on Basic Material and Asymptotics, Averaging, and Attraction. Chapters on Periodic Averaging and Hyperbolicity, Classical (first level) Normal Form Theory, Nilpotent (classical) Normal Form, and Higher Level Normal Form Theory are entirely new and represent new insights in averaging, in particular its relation with dynamical systems and the theory of normal forms. Also new are surveys on invariant manifolds in Appendix C and averaging for PDEs in Appendix E. Since the first edition, the book has expanded in length and the third author, James Murdock has been added.Review of First Edition"One of the most striking features of the book is the nice collection of examples, which range from the very simple to some that are elaborate, realistic, and of considerable practical importance. Most of them are presented in careful detail and are illustrated with profuse, illuminating diagrams." - Mathematical Reviews
Автор: Knafl Название: Adaptive Regression for Modeling Nonlinear Relationships ISBN: 3319339443 ISBN-13(EAN): 9783319339443 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes.
Описание: "Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one. " ( The American Statistician ) "The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite.
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