论文信息 - Predictions of multivariate autoregressive-moving average models

Predictions of multivariate autoregressive-moving average models

SUMMARY A simple formula for multiperiod predictions of multivariate autoregressive-moving average models is derived.The formula is explicitly given as a function of suitably defined parameter matrices and an observation vector, and includes simpler models as its special cases. The asymptotic prediction mean squared error is also derived for predictions with estimated parameters.

Taku Yamamoto | Taku Yamamoto

[1] Peter Bloomfield,et al. On the error of prediction of a time series , 1972 .

[2] Taku Yamamoto. On the Treatment of Autocorrelated Errors in the Multiperiod Prediction of Dynamic Simultaneous Equation Models , 1980 .

[3] Yoshihiro Yajima. On prediction of integrated moving average processes , 1980 .

[4] R. Baillie. PREDICTIONS FROM ARMAX MODELS , 1980 .

[5] G. T. Wilson. The Estimation of Parameters in Multivariate Time Series Models , 1973 .

[6] Andrew Harvey,et al. Maximum likelihood estimation of regression models with autoregressive-moving average disturbances , 1979 .

[7] Taku Yamamoto,et al. Asymptotic mean square prediction error for an autoregressive model with estimated coefficients , 1976 .

[8] Richard T. Baillie,et al. Asymptotic prediction mean squared error for vector autoregressive models , 1979 .

[9] H. Akaike. Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes , 1974 .