Forecasting with prediction intervals for periodic autoregressive moving average models

被引:28
|
作者
Anderson, Paul L. [1 ]
Meerschaert, Mark M. [2 ]
Zhang, Kai [2 ]
机构
[1] Albion Coll, Albion, MI 49224 USA
[2] Michigan State Univ, E Lansing, MI 48824 USA
关键词
Periodic correlation; autoregressive moving average; forecasting; TIME-SERIES; RIVER FLOWS; LIKELIHOOD; ALGORITHM;
D O I
10.1111/jtsa.12000
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
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页码:187 / 193
页数:7
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