Recursive forecasting, smoothing and seasonal adjustment of non-stationary environmental data
Version of Record online: 2 NOV 2006
Copyright © 1991 John Wiley & Sons, Ltd.
Journal of Forecasting
Volume 10, Issue 1-2, pages 57–89, January 1991
How to Cite
Young, P. C., Ng, C. N., Lane, K. and Parker, D. (1991), Recursive forecasting, smoothing and seasonal adjustment of non-stationary environmental data. J. Forecast., 10: 57–89. doi: 10.1002/for.3980100105
- Issue online: 2 NOV 2006
- Version of Record online: 2 NOV 2006
- Manuscript Revised: JAN 1990
- Manuscript Received: JAN 1989
- Component model;
- State space recursive estimation;
- Forecasting and smoothing Adaptive seasonal adjustment Atmospheric CO2
The paper presents a unified, fully recursive approach to the modelling, forecasting and seasonal adjustment of non-stationary time series and shows how it can be used as a flexible tool in the analysis of environmental data. The approach is based on time-variable parameter (TVP) versions of various well-known time-series models and exploits the suite of novel, recursive filtering and fixed interval smoothing algorithms available in the microCAPTAIN computer program. The practical utility of the analysis is demonstrated by an example based on the analysis of atmospheric CO2 and sea surface temperature anomaly data.