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Nonlinear Time Series Analysis

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

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Modelling Nonlinear Economic Time Series

This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic;

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Non-Linear Time Series

This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book;

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Recent Advances in Estimating Nonlinear Models

number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and;

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Nonlinear Econometric Modeling in Time Series Analysis

Nonlinear Econometric Modeling in Time Series presents the more recent literature on nonlinear time series. Specific topics covered with;

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Prediction of nonlinear nonstationary time series data

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Elements of Nonlinear Time Series Analysis and Forecasting

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples;

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Nonlinear Modelling of High Frequency Financial Time Series

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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Time Series Modeling of Neuroscience Data

approach, in which dynamic models of all kinds, such as linearnonlinear differential equation models and time series models, are used for;

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Exploration Of A Nonlinear World

Whittle, FRS, it celebrates Tong's path-breaking and tireless contributions to nonlinear time series analysis, chaos and statistics, by reprinting;

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Nonlinear Time Series

Designed for researchers and students, Nonlinear Times Series: Theory, Methods and Applications with R Examples familiarizes readers with;

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Complexity of Seismic Time Series

Complexity of Seismic Time Series: Measurement and Application applies the tools of nonlinear dynamics to seismic analysis, allowing;

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Nonlinear Economic Models Crosssectional, Time Series and Neural Network Applications

Nonlinear modelling has become increasingly important and widely used in economics. This valuable book brings together recent advances;

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Nonlinear Time Series Analysis with R

Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose;

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Nonlinear Stochastic Control and Filtering with Engineering-Oriented Complexities

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for;

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Nonlinear Stochastic Control and Filtering With Engineering-Oriented Complexities

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for;

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Nonlinear Ocean Waves and the Inverse Scattering Transform

of linear wave trains. Nonlinear Ocean Waves and the Inverse Scattering Transform presents the development of the nonlinear Fourier analysis;

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Time Series Analy By State Space Meth

. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance;

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Chaos and Complex Systems

Symposia in the series bring together scientists, engineers, economists and social scientists, creating a vivid forum for discussions on the latest;

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The Analysis of Time Series

, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral;

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The Analysis of Time Series

, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral;

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Statistics And Finance

Kong in July 1999. Topics covered include heavy-tailed and nonlinear continuous-time ARMA models for financial time series, and forecast;

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Nonlinear Statistical Modeling

selection models, (ii) nonparametric and semi-parametric approaches to qualitative and sample selection models, and (iii) nonlinear estimation;

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Nonlinear Time Series Analysis

which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from;

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A Nonlinear Time Series Workshop

The analysis ofwhat might be called dynamic nonlinearity in time series has its roots in the pioneering work ofBrillinger (1965) - who;

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