Practical Smoothing: The Joys of P-splines, Paul H.C. Eilers, Brian D. Marx
Автор: Chong Gu Название: Smoothing Spline ANOVA Models ISBN: 1461453682 ISBN-13(EAN): 9781461453680 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.
Автор: Chong Gu Название: Smoothing Spline ANOVA Models ISBN: 1489989846 ISBN-13(EAN): 9781489989840 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.
Автор: Han-lin Chen Название: Complex Harmonic Splines, Periodic Quasi-Wavelets ISBN: 0792361377 ISBN-13(EAN): 9780792361374 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, written by our distinguished colleague and friend, Professor Han-Lin Chen of the Institute of Mathematics, Academia Sinica, Beijing, presents, for the first time in book form, his extensive work on complex harmonic splines with applications to wavelet analysis and the numerical solution of boundary integral equations.
Автор: R. Arcang?li; Mar?a Cruz L?pez de Silanes; Juan Jo Название: Multidimensional Minimizing Splines ISBN: 1475788436 ISBN-13(EAN): 9781475788433 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is of interest to mathematicians, geologists, engineers and, in general, researchers and post graduate students involved in spline function theory, surface fitting problems or variational methods. I recommend the book to researchers in approximation theory, and to anyone interested in bivariate data fitting."
Описание: This book takes readers on a multi-perspective tour through state-of-the-art mathematical developments related to the numerical treatment of PDEs based on splines, and in particular isogeometric methods.
Автор: Chacуn Josй E., Duong Tarn Название: Multivariate Kernel Smoothing and Its Applications ISBN: 0367571730 ISBN-13(EAN): 9780367571733 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite solutions to complex data challenges.
Автор: Sergey Bagdasarov Название: Chebyshev Splines and Kolmogorov Inequalities ISBN: 3034897812 ISBN-13(EAN): 9783034897815 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Wolfgang H?rdle; Michael Schimek Название: Statistical Theory and Computational Aspects of Smoothing ISBN: 3790809306 ISBN-13(EAN): 9783790809305 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: One of the main applications of statistical smoothing techniques is nonparametric regression. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. Introduced are new developments in scatterplot smoothing and applications in statistical modelling.
Автор: Howard L. Weinert Название: Fixed Interval Smoothing for State Space Models ISBN: 0792372999 ISBN-13(EAN): 9780792372998 Издательство: Springer Рейтинг: Цена: 21655.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fixed-interval smoothing is a method of extracting information from inaccurate data. This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations collected in that interval.
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