BAYESIAN INFERENCES AND FORECASTING IN BILINEAR TIME-SERIES MODELS

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/27839

Title:	BAYESIAN INFERENCES AND FORECASTING IN BILINEAR TIME-SERIES MODELS
Authors:	CHEN,CWS
Contributors:	統計研究所
Keywords:	AUTOREGRESSIVE PROCESSES
Date:	1992
Issue Date:	2010-06-29 19:34:39 (UTC+8)
Publisher:	中央大學
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.
Relation:	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

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