Representation of Multiplicative Seasonal Vector Autoregressive Moving Average Models

Date

2009-11-01

Author

Yozgatlıgil, Ceylan

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Time series often contain observations of several variables and multivariate time series models are used to represent the relationship between these variables. There are many studies on vector autoregressive moving average (VARMA) models, but the representation of multiplicative seasonal VARMA models has not been seriously studied. In a multiplicative vector model, such as a seasonal VARMA model, the representation is not unique because of the noncommutative property of matrix multiplication. In this article, we carefully examine the consequences of different model representations on parameter estimation and forecasting through numerical illustrations, simulation, and the analysis of a housing starts and housing sales dataset.

Subject Keywords

Statistics, Probability and Uncertainty, Statistics and Probability, General Mathematics

URI

https://hdl.handle.net/11511/34644

Journal

AMERICAN STATISTICIAN

DOI

https://doi.org/10.1198/tast.2009.08040

Collections

Department of Statistics, Article

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Citation Formats

C. Yozgatlıgil, “Representation of Multiplicative Seasonal Vector Autoregressive Moving Average Models,” AMERICAN STATISTICIAN, pp. 328–334, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34644.