Bayesian inferences and forecasting in bilinear time series models
- 1 January 1992
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 21 (6) , 1725-1743
- https://doi.org/10.1080/03610929208830875
Abstract
In this paper, we propose a Bayesian approach to the analysis of bilinear time series which is an extension of Broemeling and Shaarawy's work (1988) on linear time series. The conjugate prior for parameters is used to derive the predictive distribution and the marginal posterior distribution of the bilinear parameters, by which we make inferences about the parameters and for a future observation. Our results are illustrated using the Wolf sunspot numbers from Box and Jenkins (1976) and are compared with a linear time series.Keywords
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