Электронная книга: Rong Chen «Nonlinear Time Series Analysis»
|
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. Издательство: "John Wiley&Sons Limited (USD)"
ISBN: 9781119264064 электронная книга Купить за 9105.53 руб и скачать на Litres |
Другие книги схожей тематики:
| Автор | Книга | Описание | Год | Цена | Тип книги |
|---|---|---|---|---|---|
| George E. P. Box | Time Series Analysis. Forecasting and Control | Praise for the Fourth Edition“The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to… — John Wiley&Sons Limited, электронная книга Подробнее... | 11582.49 | электронная книга | |
| Antonios Alexandridis K. | Wavelet Neural Networks. With Applications in Financial Engineering, Chaos, and Classification | A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the… — John Wiley&Sons Limited, электронная книга Подробнее... | 7953.16 | электронная книга | |
| Kairat Mynbaev T. | Short-Memory Linear Processes and Econometric Applications | This book serves as a comprehensive source of asymptotic results for econometric models with deterministic exogenous regressors. Such regressors include linear (more generally, piece-wise polynomial)… — John Wiley&Sons Limited, электронная книга Подробнее... | 11316.87 | электронная книга | |
| Wikle Christopher K. | Statistics for Spatio-Temporal Data | Winner of the 2013 DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest… — John Wiley&Sons Limited, электронная книга Подробнее... | 7020.36 | электронная книга | |
| Ligang Wu | Sliding Mode Control of Uncertain Parameter-Switching Hybrid Systems | In control theory, sliding mode control (SMC) is a nonlinear control method that alters the dynamics of a nonlinear system by application of a discontinuous control signal that forces the system to… — John Wiley&Sons Limited, электронная книга Подробнее... | 11964.9 | электронная книга |
См. также в других словарях:
Time series — Time series: random data plus trend, with best fit line and different smoothings In statistics, signal processing, econometrics and mathematical finance, a time series is a sequence of data points, measured typically at successive times spaced at … Wikipedia
Nonlinear autoregressive exogenous model — In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time series which one would like to explain or… … Wikipedia
Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… … Wikipedia
Analysis of variance — In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of… … Wikipedia
Time-scale calculus — In mathematics, time scale calculus is a unification of the theory of difference equations with that of differential equations, unifying integral and differential calculus with the calculus of finite differences, offering a formalism for studying … Wikipedia
Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… … Wikipedia
