Автор: Alexandre B. Tsybakov Название: Introduction to Nonparametric Estimation ISBN: 0387790519 ISBN-13(EAN): 9780387790510 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.
Автор: Henderson Название: Applied Nonparametric Econometrics ISBN: 0521279682 ISBN-13(EAN): 9780521279680 Издательство: Cambridge Academ Рейтинг: Цена: 6653.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians, discussing basic to advanced nonparametric methods with applications.
Автор: Ghosal, Subhashis. Название: Fundamentals of Nonparametric Bayesian Inference ISBN: 0521878268 ISBN-13(EAN): 9780521878265 Издательство: Cambridge Academ Рейтинг: Цена: 12989.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.
Автор: Rue Название: Gaussian Markov Random Fields ISBN: 1584884320 ISBN-13(EAN): 9781584884323 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Gaussian Markov Random Field (GMRF) models, most widely used in spatial statistics are presented in this, the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects.
Автор: S. Henley Название: Nonparametric Geostatistics ISBN: 9400981198 ISBN-13(EAN): 9789400981195 Издательство: Springer Рейтинг: Цена: 18860.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes computational problems related to kernel density estimation (KDE)-one of the most important and widely used data smoothing techniques. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects.
Автор: Jeffrey Hart Название: Nonparametric Smoothing and Lack-of-Fit Tests ISBN: 1475727240 ISBN-13(EAN): 9781475727241 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of the use of smoothing methods in testing the fit of parametric regression models.
Автор: Muller, P., Quintana, F.A., Jara, A., Hanson, T. Название: Bayesian Nonparametric Data Analysis ISBN: 3319189670 ISBN-13(EAN): 9783319189673 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.
Описание: This book provides theory, open source R implementations, and the latest tools for reproducible nonparametric econometric research. Advanced undergraduate students, graduate students, and faculty wishing to keep abreast of this field will find this resource more accessible than similar books.
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