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Multiple time series models

Author: Patrick T Brandt; John T Williams
Publisher: Thousand Oaks, Calif. : Sage Publications, ©2007.
Series: Quantitative applications in the social sciences, no. 07-148.
Edition/Format:   Book : EnglishView all editions and formats
Database:WorldCat
Summary:
"Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data, including simultaneous equations, ARIMA, error correction models, and vector autoregression. Authors Patrick T. Brandt and John T. Williams focus on vector autoregression (VAR) models as a generalization of these other approaches and discuss specification, estimation, and inference  Read more...
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Additional Physical Format: Online version:
Brandt, Patrick T.
Multiple time series models.
Thousand Oaks, Calif. : Sage Publications, c2007
(OCoLC)647657794
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Patrick T Brandt; John T Williams
ISBN: 1412906563 9781412906562
OCLC Number: 65341030
Description: xiii, 99 p. : ill. ; 22 cm.
Contents: Introduction to multiple time series models --
Basic vector autoregression models --
Examples of VAR analyses --
Appendix : Software for multiple time series models.
Series Title: Quantitative applications in the social sciences, no. 07-148.
Responsibility: Patrick T. Brandt, John T. Williams.
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Abstract:

Reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. This book focuses on vector autoregression  Read more...

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"This book amazingly introduces multiple time series on varied levels to help the reader to understand their assumptions, their four approaches, how to build theories to accompany their modeling, and Read more...

 
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schema:reviewBody""Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data, including simultaneous equations, ARIMA, error correction models, and vector autoregression. Authors Patrick T. Brandt and John T. Williams focus on vector autoregression (VAR) models as a generalization of these other approaches and discuss specification, estimation, and inference using these models." "This text is intended for advanced undergraduate and graduate courses on time series analysis, quantitative research methods, or more advanced statistics, especially in the departments of Sociology, Psychology, Political Science, and Economics. It is also an excellent resource for researchers in the social sciences who are conducting time series analysis or econometric studies."--Jacket."
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