Temporal Aggregation and Spurious Instantaneous Causality in Multiple Time Series Models PDF Download
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Author: Jorg Breitung
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Large aggregation interval asymptotics are used to investigate the relation between Granger causalityin disaggregated vector autoregressions (VARs) and associated contemporaneous correlation among innovations of the aggregated system. One of our main contributions is that we outline various conditions under which the informational content of error covariance matrices yields insight into the causal structure of the VAR. Monte Carlo results suggest that our asymptotic findings are applicable even when the aggregation interval is small, as long as the time series are not characterized by high levels of persistence.
Author: Jorg Breitung
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Large aggregation interval asymptotics are used to investigate the relation between Granger causalityin disaggregated vector autoregressions (VARs) and associated contemporaneous correlation among innovations of the aggregated system. One of our main contributions is that we outline various conditions under which the informational content of error covariance matrices yields insight into the causal structure of the VAR. Monte Carlo results suggest that our asymptotic findings are applicable even when the aggregation interval is small, as long as the time series are not characterized by high levels of persistence.
Author: Andrea Silvestrini
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 68
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Author: Jörg Breitung
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
Author: William W. S. Wei
Publisher: John Wiley & Sons
ISBN: 1119502853
Category : Mathematics
Languages : en
Pages : 536
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Book Description
An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.
Author: G. Elliott
Publisher: Elsevier
ISBN: 0444513957
Category : Business & Economics
Languages : en
Pages : 1071
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Book Description
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Author: Francesco Palumbo
Publisher: Springer Science & Business Media
ISBN: 3642037399
Category : Mathematics
Languages : en
Pages : 473
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Book Description
The volume provides results from the latest methodological developments in data analysis and classification and highlights new emerging subjects within the field. It contains articles about statistical models, classification, cluster analysis, multidimensional scaling, multivariate analysis, latent variables, knowledge extraction from temporal data, financial and economic applications, and missing values. Papers cover both theoretical and empirical aspects.
Author: Esther Florin
Publisher: Forschungszentrum Jülich
ISBN: 3893366466
Category :
Languages : en
Pages : 257
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Book Description
Author: Kees van Montfort
Publisher: Springer
ISBN: 3319772198
Category : Medical
Languages : en
Pages : 442
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Book Description
This unique book provides an overview of continuous time modeling in the behavioral and related sciences. It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable. One main issue is the dependence of discrete time parameter estimates on the chosen time interval, which leads to incomparability of results across different observation intervals. Continuous time modeling by means of differential equations offers a powerful approach for studying dynamic phenomena, yet the use of this approach in the behavioral and related sciences such as psychology, sociology, economics and medicine, is still rare. This is unfortunate, because in these fields often only a few discrete time (sampled) observations are available for analysis (e.g., daily, weekly, yearly, etc.). However, as emphasized by Rex Bergstrom, the pioneer of continuous-time modeling in econometrics, neither human beings nor the economy cease to exist in between observations. In 16 chapters, the book addresses a vast range of topics in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling techniques. Each chapter describes the type of research questions and data that the approach is most suitable for, provides detailed statistical explanations of the models, and includes one or more applied examples. To allow readers to implement the various techniques directly, accompanying computer code is made available online. The book is intended as a reference work for students and scientists working with longitudinal data who have a Master's- or early PhD-level knowledge of statistics.
Author: Helmut Lütkepohl
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 574
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Book Description
Author:
Publisher:
ISBN:
Category : Business cycles
Languages : en
Pages : 442
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Book Description
