Temporal aggregation in the multivariate regression model

Temporal aggregation in the multivariate regression model PDF Author: John Geweke
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 47

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Book Description

Temporal aggregation in the multivariate regression model

Temporal aggregation in the multivariate regression model PDF Author: John Geweke
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 47

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Book Description


Temporal Aggregation and Related Problems in Multivariate Time Series Analysis

Temporal Aggregation and Related Problems in Multivariate Time Series Analysis PDF Author: Ceylan Yozgatligil
Publisher:
ISBN: 9781109933444
Category : Statistics
Languages : en
Pages : 225

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Book Description
The time series data used are generally sums over time of data generated more frequently than the reporting interval. In this research, we focused on the effect of temporal aggregation on a vector autoregressive moving average (VARMA) model structure, a cointegration relationship, the causality, and multiplicative seasonal VARMA processes.

Temporal Aggregation of Univariate and Multivariate Time Series Models

Temporal Aggregation of Univariate and Multivariate Time Series Models PDF Author: Andrea Silvestrini
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 68

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Effect of Temporal Aggregation on Multiple Time Series in the Frequency Domain

Effect of Temporal Aggregation on Multiple Time Series in the Frequency Domain PDF Author: Uwe Hassler
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The effect of temporal aggregation on bivariate spectral measures is investigated. First, the low-frequency regression coefficient turns out to be invariant under aggregation irrespective of differencing, with the exception of when the aggregation of flow and stock variables is combined. Second, the long-run squared coherency is invariant with respect to aggregation irrespective of differencing. Third, for frequencies different from zero, limiting results for a growing aggregation level m are obtained equal to those at frequency 0 of the underlying basic series. Hence, all frequency domain information is distorted by aggregation apart from the long-run one. This also holds true for the phase angle that always approaches zero with growing aggregation level m. The sole exception to these findings is the case of the skip sampling stationary series. Moreover, for finite aggregation level, one may exactly quantify the aggregational effect on each cycle of interest. Numerical examples illustrate our results.

Multivariate Time Series Analysis and Applications

Multivariate Time Series Analysis and Applications PDF 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.

Temporal Aggregation of Multivariate GARCH Processes

Temporal Aggregation of Multivariate GARCH Processes PDF Author: Christian M. Hafner
Publisher:
ISBN:
Category :
Languages : en
Pages : 43

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Effect of Temporal Aggregation on the Dynamic Relationship of Two Time Series Variables

Effect of Temporal Aggregation on the Dynamic Relationship of Two Time Series Variables PDF Author: G. C. Tiao
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 36

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Temporal Aggregation, the Data Interval Bias and Empirical Estimation of Bimonthly Relations from Annual Data

Temporal Aggregation, the Data Interval Bias and Empirical Estimation of Bimonthly Relations from Annual Data PDF Author: Frank Myron Bass
Publisher:
ISBN:
Category : Advertising
Languages : en
Pages : 44

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Temporal Aggregation and Causality in Multiple Time Series Models

Temporal Aggregation and Causality in Multiple Time Series Models PDF Author: Jörg Breitung
Publisher:
ISBN:
Category :
Languages : en
Pages : 33

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The Effect of Temporal Aggregation on Discrete Dynamic Time Series Models

The Effect of Temporal Aggregation on Discrete Dynamic Time Series Models PDF Author: William W. S. Wei
Publisher:
ISBN:
Category :
Languages : en
Pages : 342

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Book Description