search query: @indexterm STATISTICAL METHODS / total: 745
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| Author: | Ng, C. N. Young, P. C. |
| Title: | Recursive estimation and forecasting of non-stationary time series |
| Journal: | Journal of Forecasting
1990 : MAR-APR, VOL.9:2, p.173-204 |
| Index terms: | TIME SERIES FORECASTING ESTIMATION STATISTICAL METHODS MODELS SEASONAL FLUCTUATION |
| Language: | eng |
| Abstract: | A unified, fully recursive approach to the modelling and forecasting of non-stationary time series is presented. The basic time-series model, which is based on the well-known "component" or "structural" form, is formulated in state-space terms. A novel spectral decomposition procedure, based on the exploitation of recursive smoothing algorithms, is utilized to simplify the procedures of model identification and estimation. Finally, the fully recursive formulation allows for conventional or self-adaptive implementation of state-space forecasting and seasonal adjustment. The basic approach can be extended to handle explanatory variables or full multivariable (vector) series. |
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