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Nonlinear Time Series Analysis, Tsay, Ruey S.,


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Цена: 18208.00р.
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Автор: Tsay, Ruey S.,
Название:  Nonlinear Time Series Analysis
Перевод названия: Цай: Нелинейный анализ временных рядов
ISBN: 9781119264057
Издательство: Wiley
Классификация:

ISBN-10: 1119264057
Обложка/Формат: Hardback
Страницы: 512
Вес: 0.67 кг.
Дата издания: 30.11.2018
Серия: Wiley series in probability and statistics
Язык: English
Размер: 161 x 236 x 30
Читательская аудитория: Professional & vocational
Ключевые слова: Economics,Mathematics
Основная тема: Time Series
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание:

A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis

Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors--noted experts in the field--explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models.

The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide:

- Offers research developed by leading scholars of time series analysis

- Presents R commands making it possible to reproduce all the analyses included in the text

- Contains real-world examples throughout the book

- Recommends exercises to test understanding of material presented

- Includes an instructor solutions manual and companion website

Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.




Time Series Analysis by State Space Methods

Автор: Durbin, James; Koopman, Siem Jan
Название: Time Series Analysis by State Space Methods
ISBN: 019964117X ISBN-13(EAN): 9780199641178
Издательство: Oxford Academ
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Цена: 18216.00 р.
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Описание: This new edition updates Durbin & Koopman`s important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.

Time Series Analysis for the Social Sciences

Автор: Box-Steffensmeier
Название: Time Series Analysis for the Social Sciences
ISBN: 0521691559 ISBN-13(EAN): 9780521691550
Издательство: Cambridge Academ
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Цена: 4592.00 р.
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Описание: Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. The book covers ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting.

Nonlinear Time Series / Nonparametric and Parametric Methods

Автор: Fan Jianqing, Yao Qiwei
Название: Nonlinear Time Series / Nonparametric and Parametric Methods
ISBN: 0387261427 ISBN-13(EAN): 9780387261423
Издательство: Springer
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Цена: 15372.00 р.
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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.

Mathematical methods in time series analysis and digital image processing

Автор: Dahlhaus
Название: Mathematical methods in time series analysis and digital image processing
ISBN: 3540756310 ISBN-13(EAN): 9783540756316
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Intends to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. This book summarizes work carried out in the field of theoretical signal and image processing.

Time Series Analysis for the Social Sciences

Автор: Box-Steffensmeier
Название: Time Series Analysis for the Social Sciences
ISBN: 0521871166 ISBN-13(EAN): 9780521871167
Издательство: Cambridge Academ
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Цена: 12355.00 р.
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Описание: Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. The book covers ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting.

An Introduction to Bispectral Analysis and Bilinear Time Series Models

Автор: T.S. Rao; M.M. Gabr
Название: An Introduction to Bispectral Analysis and Bilinear Time Series Models
ISBN: 0387960392 ISBN-13(EAN): 9780387960395
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The theory of time series models has been well developed over the last thirt,y years. The most interesting feature of such a model is that its second order covariance analysis is ve~ similar to that for a linear model. This demonstrates the importance of higher order covariance analysis for nonlinear models.

Time Series Analysis of Irregularly Observed Data

Автор: E. Parzen
Название: Time Series Analysis of Irregularly Observed Data
ISBN: 0387960406 ISBN-13(EAN): 9780387960401
Издательство: Springer
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Цена: 14673.00 р.
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Описание: The symposium aimed to provide a review of the state of the art, define outstanding problems for research by theoreticians, transmit to practitioners recently developed algorithms, and stimulate interaction between statisticians and researchers in subject matter fields.

The Analysis of Time Series: Theory and Practice

Автор: Christopher Chatfield
Название: The Analysis of Time Series: Theory and Practice
ISBN: 0412141809 ISBN-13(EAN): 9780412141805
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Time-series analysis is an area of statistics which is of particular interest at the present time. Throughout the book, references are usually given to recent readily accessible books and journals rather than to the original attributive references.

Time Series Analysis and Applications to Geophysical Systems

Автор: David Brillinger; Enders Anthony Robinson; Frederi
Название: Time Series Analysis and Applications to Geophysical Systems
ISBN: 1441919716 ISBN-13(EAN): 9781441919717
Издательство: Springer
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Цена: 25155.00 р.
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Описание: Arnold, Director of the IMA Fadil Santosa, Deputy Director of the IMA v PREFACE This volume contains a collection of papers that were presented dur- ing the Workshop on Time Series Analysis and Applications to Geophysical Systems at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota from November 12-15, 2001.

Nonlinear Time Series Analysis

Автор: Holger Kantz
Название: Nonlinear Time Series Analysis
ISBN: 0521529026 ISBN-13(EAN): 9780521529020
Издательство: Cambridge Academ
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Цена: 12355.00 р.
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Описание: The time variability of many natural and social phenomena is not well described by standard methods of data analysis. Nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand such seemingly unpredictable behaviour. Results are applied to real data from physics, biology, medicine and engineering.

Nonlinear Analysis and Prediction of Time Series in Multiphase Reactors

Автор: Mingyan Liu; Zongding Hu
Название: Nonlinear Analysis and Prediction of Time Series in Multiphase Reactors
ISBN: 3319041924 ISBN-13(EAN): 9783319041926
Издательство: Springer
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Цена: 9141.00 р.
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Описание: They present qualitative and quantitative non-linear analysis tools which include attractor phase plane plot, correlation dimension, Kolmogorov entropy and largest Lyapunov exponent calculations and local non-linear short-term prediction.

Robust and Nonlinear Time Series Analysis

Автор: J. Franke; W. H?rdle; D. Martin
Название: Robust and Nonlinear Time Series Analysis
ISBN: 038796102X ISBN-13(EAN): 9780387961026
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data.


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