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Multiple time series models

Patrick T. Brandt · 2006

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About the book

"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."--BOOK JACKET

Book details

Year
2006
Language
English
Publisher
Sage Publications, Inc
Editions
4
Pages
120
ISBN
9781412906562

Data source: Wikidata