Nonlinear Time Series

Nonlinear Time Series Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Nonlinear Time Series book. This book definitely worth reading, it is an incredibly well-written.

Nonlinear Time Series Analysis

Holger Kantz,Thomas Schreiber
Nonlinear Time Series Analysis Book PDF

Author : Holger Kantz,Thomas Schreiber
Publisher : Cambridge University Press
Page : 390 pages
File Size : 44,8 Mb
Release : 2004
Category : Mathematics
ISBN : 0521529026

Get Book

Nonlinear Time Series Analysis by Holger Kantz,Thomas Schreiber Pdf

The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems 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 real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.

Nonlinear Time Series

Randal Douc,Eric Moulines,David Stoffer
Nonlinear Time Series Book PDF

Author : Randal Douc,Eric Moulines,David Stoffer
Publisher : CRC Press
Page : 548 pages
File Size : 54,5 Mb
Release : 2014-01-06
Category : Mathematics
ISBN : 9781466502345

Get Book

Nonlinear Time Series by Randal Douc,Eric Moulines,David Stoffer Pdf

This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.

Nonlinear Time Series Analysis

Ruey S. Tsay,Rong Chen
Nonlinear Time Series Analysis Book PDF

Author : Ruey S. Tsay,Rong Chen
Publisher : John Wiley & Sons
Page : 512 pages
File Size : 42,6 Mb
Release : 2018-09-14
Category : Mathematics
ISBN : 9781119264071

Get Book

Nonlinear Time Series Analysis by Ruey S. Tsay,Rong Chen Pdf

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.

Elements of Nonlinear Time Series Analysis and Forecasting

Jan G. De Gooijer
Elements of Nonlinear Time Series Analysis and Forecasting Book PDF

Author : Jan G. De Gooijer
Publisher : Springer
Page : 618 pages
File Size : 54,8 Mb
Release : 2017-03-30
Category : Mathematics
ISBN : 9783319432526

Get Book

Elements of Nonlinear Time Series Analysis and Forecasting by Jan G. De Gooijer Pdf

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.

Nonlinear Time Series

Jianqing Fan,Qiwei Yao
Nonlinear Time Series Book PDF

Author : Jianqing Fan,Qiwei Yao
Publisher : Springer Science & Business Media
Page : 565 pages
File Size : 48,9 Mb
Release : 2008-09-11
Category : Mathematics
ISBN : 9780387693958

Get Book

Nonlinear Time Series by Jianqing Fan,Qiwei Yao Pdf

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Nonlinear Time Series Analysis with R

Ray Huffaker,Marco Bittelli,Rodolfo Rosa
Nonlinear Time Series Analysis with R Book PDF

Author : Ray Huffaker,Marco Bittelli,Rodolfo Rosa
Publisher : Oxford University Press
Page : 312 pages
File Size : 41,7 Mb
Release : 2017-10-20
Category : Mathematics
ISBN : 9780191085796

Get Book

Nonlinear Time Series Analysis with R by Ray Huffaker,Marco Bittelli,Rodolfo Rosa Pdf

Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose whether highly fluctuating and random appearing data are most likely driven by random or deterministic dynamic forces. It joins the chorus of voices recommending 'getting to know your data' as an essential preliminary evidentiary step in modelling. Time series are often highly fluctuating with a random appearance. Observed volatility is commonly attributed to exogenous random shocks to stable real-world systems. However, breakthroughs in nonlinear dynamics raise another possibility: highly complex dynamics can emerge endogenously from astoundingly parsimonious deterministic nonlinear models. Nonlinear Time Series Analysis (NLTS) is a collection of empirical tools designed to aid practitioners detect whether stochastic or deterministic dynamics most likely drive observed complexity. Practitioners become 'data detectives' accumulating hard empirical evidence supporting their modelling approach. This book is targeted to professionals and graduate students in engineering and the biophysical and social sciences. Its major objectives are to help non-mathematicians — with limited knowledge of nonlinear dynamics — to become operational in NLTS; and in this way to pave the way for NLTS to be adopted in the conventional empirical toolbox and core coursework of the targeted disciplines. Consistent with modern trends in university instruction, the book makes readers active learners with hands-on computer experiments in R code directing them through NLTS methods and helping them understand the underlying logic (please see www.marco.bittelli.com). The computer code is explained in detail so that readers can adjust it for use in their own work. The book also provides readers with an explicit framework — condensed from sound empirical practices recommended in the literature — that details a step-by-step procedure for applying NLTS in real-world data diagnostics.

Threshold Models in Non-linear Time Series Analysis

H. Tong
Threshold Models in Non linear Time Series Analysis Book PDF

Author : H. Tong
Publisher : Springer Science & Business Media
Page : 333 pages
File Size : 51,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781468478884

Get Book

Threshold Models in Non-linear Time Series Analysis by H. Tong Pdf

In the last two years or so, I was most fortunate in being given opportunities of lecturing on a new methodology to a variety of audiences in Britain, China, Finland, France and Spain. Despite my almost Confucian attitude of preferring talking (i.e. a transient record) to writing (i.e. a permanent record), the warm encouragement of friends has led to the ensuing notes. I am also only too conscious of the infancy of the methodology introduced in these notes. However, it is my sincere hope that exposure to a wider audience will accelerate its maturity. Readers are assumed to be familiar with the basic theory of time series analysis. The book by Professor M.B. Priestley (1981) may be used as a general reference. Chapter One is addressed to the general question: "why do we need non-linear time series models?" After describing some significant advantages of linear models, it singles out several major limitations of linearity. Of course, the selection reflects my personal view on the subject, which is only at its very beginning, although there does seem to be a general agreement in the literature that time irr'eversibility and limit cycles are among the most obvious.

Nonlinear Time Series

Jiti Gao
Nonlinear Time Series Book PDF

Author : Jiti Gao
Publisher : CRC Press
Page : 237 pages
File Size : 40,7 Mb
Release : 2007-03-22
Category : Mathematics
ISBN : 1420011219

Get Book

Nonlinear Time Series by Jiti Gao Pdf

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully nonparametric models and methods. Answering the call for an up-to-date overview of the latest developments in the field, Nonlinear Time Series: Semiparametric and Nonparametric Methods focuses on various semiparametric methods in model estimation, specification testing, and selection of time series data. After a brief introduction, the book examines semiparametric estimation and specification methods and then applies these approaches to a class of nonlinear continuous-time models with real-world data. It also assesses some newly proposed semiparametric estimation procedures for time series data with long-range dependence. Even though the book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real-world data in many disciplines. This resource covers key methods in time series analysis and provides the necessary theoretical details. The latest applied finance and financial econometrics results and applications presented in the book enable researchers and graduate students to keep abreast of developments in the field.

Non-Linear Time Series Models in Empirical Finance

Philip Hans Franses,Dick van Dijk
Non Linear Time Series Models in Empirical Finance Book PDF

Author : Philip Hans Franses,Dick van Dijk
Publisher : Cambridge University Press
Page : 299 pages
File Size : 47,6 Mb
Release : 2000-07-27
Category : Business & Economics
ISBN : 9780521770415

Get Book

Non-Linear Time Series Models in Empirical Finance by Philip Hans Franses,Dick van Dijk Pdf

This 2000 volume reviews non-linear time series models, and their applications to financial markets.

Applied Nonlinear Time Series Analysis

Michael Small
Applied Nonlinear Time Series Analysis Book PDF

Author : Michael Small
Publisher : World Scientific
Page : 262 pages
File Size : 45,9 Mb
Release : 2005
Category : Mathematics
ISBN : 9789812561176

Get Book

Applied Nonlinear Time Series Analysis by Michael Small Pdf

A collection of photographs focusing on the fading traditions, heritage and culture in County Cork Ireland.

Topics in Nonlinear Time Series Analysis

Andreas Galka
Topics in Nonlinear Time Series Analysis Book PDF

Author : Andreas Galka
Publisher : World Scientific
Page : 360 pages
File Size : 43,6 Mb
Release : 2000-02-18
Category : Science
ISBN : 9789814493925

Get Book

Topics in Nonlinear Time Series Analysis by Andreas Galka Pdf

This book provides a thorough review of a class of powerful algorithms for the numerical analysis of complex time series data which were obtained from dynamical systems. These algorithms are based on the concept of state space representations of the underlying dynamics, as introduced by nonlinear dynamics. In particular, current algorithms for state space reconstruction, correlation dimension estimation, testing for determinism and surrogate data testing are presented — algorithms which have been playing a central role in the investigation of deterministic chaos and related phenomena since 1980. Special emphasis is given to the much-disputed issue whether these algorithms can be successfully employed for the analysis of the human electroencephalogram. Contents:Dynamical Systems, Time Series and AttractorsLinear MethodsState Space Reconstruction: Theoretical FoundationsState Space Reconstruction: Practical ApplicationDimensions: Basic DefinitionsLyapunov Exponents and EntropiesNumerical Estimation of the Correlation DimensionSources of Error and Data Set Size RequirementsMonte Carlo Analysis of Dimension EstimationSurrogate Data TestsDimension Analysis of the Human EEGTesting for Determinism in Time Series Readership: Graduates and scientists in physics, applied mathematics, neurology, theoretical biology, economics, meteorology and neuroinformatics. Keywords:Time Series Analysis;Nonlinear Dynamics;Fractal Dimension;Correlation Dimension;Chaos;Electroencephalogram;EEG;Determinism;Strange Attractor;Embedding;Attractor Reconstruction;Surrogate DataReviews: “The book is pleasantly written and makes for easy reading. It is informative for anyone with a sufficiently deep knowledge of nonlinear dynamics.” Mathematical Reviews

Modelling Nonlinear Economic Time Series

Timo Teräsvirta,Dag Tjøstheim,Clive W. J. Granger
Modelling Nonlinear Economic Time Series Book PDF

Author : Timo Teräsvirta,Dag Tjøstheim,Clive W. J. Granger
Publisher : OUP Oxford
Page : 592 pages
File Size : 49,8 Mb
Release : 2010-12-16
Category : Business & Economics
ISBN : 0199587140

Get Book

Modelling Nonlinear Economic Time Series by Timo Teräsvirta,Dag Tjøstheim,Clive W. J. Granger Pdf

This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.

Non-linear Time Series

Howell Tong
Non linear Time Series Book PDF

Author : Howell Tong
Publisher : Oxford University Press, USA
Page : 592 pages
File Size : 50,9 Mb
Release : 1990
Category : Mathematics
ISBN : MINN:31951D00520332J

Get Book

Non-linear Time Series by Howell Tong Pdf

Written by an internationally recognized expert in the field, this book provides a valuable introduction to the rapidly growing area of non-linear time series. Because developments in the study of dynamical systems have motivated many of the advances discussed here, the author's coverage includes such fundamental concepts of dynamical systems theory as limit cycles, Lyapunov functions, thresholds, and stability, with detailed descriptions of their role in the analysis of non-linear time series data. As the first accessible and comprehensive account of these exciting new developments, this unique volume bridges the gap between linear and chaotic time series analysis. Both statisticians and dynamical systems theorists will value its survey of recent developments and the present state of research, as well as the discussion of a number of unsolved problems in the field.

Nonlinear Time Series Analysis of Business Cycles

C. Milas,P. A. Rothman,Dick van Dijk,David E. Wildasin
Nonlinear Time Series Analysis of Business Cycles Book PDF

Author : C. Milas,P. A. Rothman,Dick van Dijk,David E. Wildasin
Publisher : Emerald Group Publishing
Page : 461 pages
File Size : 46,9 Mb
Release : 2006-02-08
Category : Business & Economics
ISBN : 9780444518385

Get Book

Nonlinear Time Series Analysis of Business Cycles by C. Milas,P. A. Rothman,Dick van Dijk,David E. Wildasin Pdf

This volume of Contributions to Economic Analysis addresses a number of important questions in the field of business cycles including: How should business cycles be dated and measured? What is the response of output and employment to oil-price and monetary shocks? And, is the business cycle asymmetric, and does it matter?

Nonlinear Modeling of Solar Radiation and Wind Speed Time Series

Luigi Fortuna,Giuseppe Nunnari,Silvia Nunnari
Nonlinear Modeling of Solar Radiation and Wind Speed Time Series Book PDF

Author : Luigi Fortuna,Giuseppe Nunnari,Silvia Nunnari
Publisher : Springer
Page : 98 pages
File Size : 48,7 Mb
Release : 2016-06-21
Category : Technology & Engineering
ISBN : 9783319387642

Get Book

Nonlinear Modeling of Solar Radiation and Wind Speed Time Series by Luigi Fortuna,Giuseppe Nunnari,Silvia Nunnari Pdf

This brief is a clear, concise description of the main techniques of time series analysis —stationary, autocorrelation, mutual information, fractal and multifractal analysis, chaos analysis, etc.— as they are applied to the influence of wind speed and solar radiation on the production of electrical energy from these renewable sources. The problem of implementing prediction models is addressed by using the embedding-phase-space approach: a powerful technique for the modeling of complex systems. Readers are also guided in applying the main machine learning techniques for classification of the patterns hidden in their time series and so will be able to perform statistical analyses that are not possible by using conventional techniques. The conceptual exposition avoids unnecessary mathematical details and focuses on concrete examples in order to ensure a better understanding of the proposed techniques. Results are well-illustrated by figures and tables.