Modeling Multiple Time Series with Applications
Abstract
An approach to the modeling and analysis of multiple time series is proposed. Properties of a class of vector autoregressive moving average models are discussed. Modeling procedures consisting of tentative specification, estimation, and diagnostic checking are outlined and illustrated by three real examples.
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“To capture dependencies, we use a standard multivariate time series framework due to Box and Jenkins (cf., Tiao & Box, 1981).”
Method
- Authors
- Tiao, G. C., & Box, G. E. P.
- Affiliations
- University of Wisconsin System (US)
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1981-12
- Volume
- 76
- Issue
- 376
- Pages
- 802-816
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2026181456
- Cited by
- 626
- References
- 0
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 8 · 2023: 3 · 2022: 6 · 2021: 13 · 2020: 15 · 2019: 13 · 2018: 16 · 2017: 13 · 2016: 7 · 2015: 17 · 2014: 21 · 2013: 15 · 2012: 14
- FWCI
- 31.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- multiple time series, vector autoregressive moving average models, VARMA models, model specification, model estimation, diagnostic checking
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