Автор: Fan Jianqing, Yao Qiwei Название: Nonlinear Time Series / Nonparametric and Parametric Methods ISBN: 0387261427 ISBN-13(EAN): 9780387261423 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal of Statistics.
Описание: This volume introduces a variety of combined parametric-nonparametric algorithms aimed at resolving problems with block-oriented non-linear dynamic system identification in the presence of random disturbances. It includes analysis of their limit properties.
Автор: Xue Yifeng Название: Stable Perturbations Of Operators And Related Topics ISBN: 9814383597 ISBN-13(EAN): 9789814383592 Издательство: World Scientific Publishing Рейтинг: Цена: 15048.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A collection of articles that covers topics that range from Markov processes, backward stochastic differential equations, stochastic partial differential equations, stochastic control, potential theory, functional inequalities, optimal stopping, portfolio selection, to risk measure and risk theory.
Автор: S. Zlobec Название: Stable Parametric Programming ISBN: 1461348854 ISBN-13(EAN): 9781461348856 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a study of these notions and their relationship in linear and convex parametric programming models. Then new results in convex programming, using LFS functions, for single-objective, multi-objective, differentiable and non-smooth programs are introduced.
Автор: Kanife Paul Obiora Название: Computer Aided Virtual Manufacturing Using Creo Parametric ISBN: 3319233580 ISBN-13(EAN): 9783319233581 Издательство: Springer Рейтинг: Цена: 13060.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer Aided Virtual Manufacturing Using Creo Parametric
Автор: PARAMETRIC; BROSOWSKI; DEUTSCH Название: Parametric Optimization and Approximation ISBN: 3034862555 ISBN-13(EAN): 9783034862554 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Ulhas Jayram Dixit Название: Examples in Parametric Inference with R ISBN: 9811008884 ISBN-13(EAN): 9789811008887 Издательство: Springer Рейтинг: Цена: 9362.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests.
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis and related fields.
Specific topics covered include:
* non-parametric estimation of lifetimes of subjects exposed to radiation
* statistical analysis of simultaneous degradation-mortality data with covariates of the aged
* estimation of maintenance efficiency in semiparametric imperfect repair models
* cancer prognosis using survival forests
* short-term health problems related to air pollution: analysis using semiparametric generalized additive models
* parametric models in accelerated life testing and fuzzy data
* semiparametric models in the studies of aging and longevity
This book will be of use as a reference text for general statisticians, theoreticians, graduate students, reliability engineers, health researchers, and biostatisticians working in applied probability and statistics.
Автор: S.S. Ge; C.C. Hang; T.H. Lee; Tao Zhang Название: Stable Adaptive Neural Network Control ISBN: 1441949321 ISBN-13(EAN): 9781441949325 Издательство: Springer Рейтинг: Цена: 28732.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a rapid development of neural network control tech- niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec- tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.
Описание: This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity.
Автор: Chueshov, Igor Название: Dynamics of quasi-stable dissipative systems ISBN: 3319229028 ISBN-13(EAN): 9783319229027 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Dynamics of Quasi-Stable Dissipative Systems
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