An Introduction to Bilinear Time Series Models PDF Download
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Author: Clive William John Granger
Publisher:
ISBN: 9783525112397
Category : Série chronologique
Languages : en
Pages : 94
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Book Description
Non-linear time series models; Bilinear models in economics; Methodology of time series analysis; The general bilinear model and stability analysis; Superdiagonal models; Diagonal models; Subdiagonal and other models; Forecasting and invertibility; Estimation and applications.
Author: Clive William John Granger
Publisher:
ISBN: 9783525112397
Category : Série chronologique
Languages : en
Pages : 94
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Book Description
Non-linear time series models; Bilinear models in economics; Methodology of time series analysis; The general bilinear model and stability analysis; Superdiagonal models; Diagonal models; Subdiagonal and other models; Forecasting and invertibility; Estimation and applications.
Author: T.S. Rao
Publisher: Springer Science & Business Media
ISBN: 1468463187
Category : Mathematics
Languages : en
Pages : 289
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Book Description
The theory of time series models has been well developed over the last thirt,y years. Both the frequenc.y domain and time domain approaches have been widely used in the analysis of linear time series models. However. many physical phenomena cannot be adequately represented by linear models; hence the necessity of nonlinear models and higher order spectra. Recently a number of nonlinear models have been proposed. In this monograph we restrict attention to one particular nonlinear model. known as the "bilinear model". 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. For bilinear models it is also possible to obtain analytic expressions for covariances. spectra. etc. which are often difficult to obtain for other proposed nonlinear models. Estimation of bispectrum and its use in the construction of tests for linearit,y and symmetry are also discussed. All the methods are illustrated with simulated and real data. The first author would like to acknowledge the benefit he received in the preparation of this monograph from delivering a series of lectures on the topic of bilinear models at the University of Bielefeld. Ecole Normale Superieure. University of Paris (South) and the Mathematisch Cen trum. Ams terdam.
Author: A. Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Chris Chatfield
Publisher: CRC Press
ISBN: 1498795641
Category : Mathematics
Languages : en
Pages : 398
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Book Description
This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models. It also presents many examples and implementations of time series models and methods to reflect advances in the field. Highlights of the seventh edition: A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.
Author: György Terdik
Publisher: Springer Science & Business Media
ISBN: 1461215528
Category : Mathematics
Languages : en
Pages : 275
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Book Description
The object of the present work is a systematic statistical analysis of bilinear processes in the frequency domain. The first two chapters are devoted to the basic theory of nonlinear functions of stationary Gaussian processes, Hermite polynomials, cumulants and higher order spectra, multiple Wiener-Itô integrals and finally chaotic Wiener-Itô spectral representation of subordinated processes. There are two chapters for general nonlinear time series problems.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Christopher Chatfield
Publisher: Chapman & Hall
ISBN:
Category : Mathematics
Languages : en
Pages : 306
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Book Description
Simple descriptive techniques; Probability models for time series; Estimation in the domain; Forecasting; Stationary processes in the frequency domain; Spectral analysis; Bivariate processes; Linear systems.
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
ISBN: 3662026910
Category : Business & Economics
Languages : en
Pages : 556
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Book Description
Author: Andrew C. Harvey
Publisher: Cambridge University Press
ISBN: 1107717140
Category : Business & Economics
Languages : en
Pages : 578
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Book Description
In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.
Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
ISBN: 1118745159
Category : Mathematics
Languages : en
Pages : 670
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Book Description
Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.
