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Date : 1999-08-16
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Nonlinear Time Series Analysis Wiley Series in ~ 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 statespace models and Bayesian as well as classical approaches to nonlinear time series analysis The authors—noted experts in the field—explore the advantages
Nonlinear Time Series Analysis Methods And Applications ~ Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand and from a statistical perspective on the other After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series time series generated by nonlinear stochastic systems and spatiotemporal dynamical systems are considered
Nonlinear Time Series Theory Methods and Applications ~ Designed for researchers and students Nonlinear Times Series Theory Methods and Applications with R Examples familiarizes readers with the principles behind nonlinear time series models―without overwhelming them with difficult mathematical developments By focusing on basic principles and theory the authors give readers the background required to craft their own stochastic models
Methods of Nonlinear Time Series Analysis and Applications ~ We present an overview of the techniques used for nonlinear time series analysis to detect nontrivial structures in such time series data that will indicate the nature of underlying dynamics that produce the data We start with the method of time delay embedding that can be used to reconstruct the dynamics in higher dimension
Methods of Nonlinear Time Series Analysis and Applications ~ While both nonlinear time series analysis and complex network theory are widely considered to be established fields of complex systems sciences with strong links to nonlinear dynamics and
Nonlinear Time Series Analysis Nonlinear Time Series and ~ Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand and from a statistical perspective on the other After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series time series generated by nonlinear stochastic systems and spatiotemporal dynamical systems are considered
Nonlinear Time Series Analysis Wiley ~ Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods nonlinear statespace 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
150307493 Nonlinear timeseries analysis revisited ~ In 1980 and 1981 two pioneering papers laid the foundation for what became known as nonlinear timeseries analysis the analysis of observed datatypically univariatevia dynamical systems theory Based on the concept of statespace reconstruction this set of methods allows us to compute characteristic quantities such as Lyapunov exponents and fractal dimensions to predict the future
Nonlinear time series analysis Encyclopedia of Mathematics ~ In the analysis of stationary time series the spectral density function if it exists is nonlinear under the above definition However for reasons to be made clear later a statistical analysis that is based on it or its equivalents is ordinarily considered a linear analysis
Nonlinear Time Series Models University of Washington ~ Nonlinear Time Series Models 181 Introduction Most of the time series models discussed in the previous chapters are linear time series models Although they remain at the forefront of academic and applied research it has often been found that simple linear time series models usually leave certain aspects of economic and financial data unexplained
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