Stationary Autoregressive Models via a Bayesian Nonparametric Approach

An approach to constructing strictly stationary AR(1)-type models with arbitrary stationary distributions and a flexible dependence structure is introduced. Bayesian nonparametric predictive density functions, based on single observations, are used to construct the one-step ahead predictive density. This is a natural and highly flexible way to model a one-step predictive/transition density. Copyright 2005 Blackwell Publishing Ltd.

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Year of publication:	2005
Authors:	Mena, Ramsés H. ; Walker, Stephen G.
Published in:	Journal of Time Series Analysis. - Wiley Blackwell, ISSN 0143-9782. - Vol. 26.2005, 6, p. 789-805
Publisher:	Wiley Blackwell

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005260657