Journal
JOURNAL OF TIME SERIES ANALYSIS
Volume 34, Issue 2, Pages 187-193Publisher
WILEY
DOI: 10.1111/jtsa.12000
Keywords
Periodic correlation; autoregressive moving average; forecasting
Funding
- NSF [DMS-1025486, DMS-0803360, EAR-0823965]
- NIH [R01-EB012079-01]
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Periodic autoregressive moving average (PARMA) models are indicated for time series whose mean, variance and covariance function vary with the season. In this study, we develop and implement forecasting procedures for PARMA models. Forecasts are developed using the innovations algorithm, along with an idea of Ansley. A formula for the asymptotic error variance is provided, so that Gaussian prediction intervals can be computed. Finally, an application to monthly river flow forecasting is given, to illustrate the method.
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