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.
Year of publication: |
2005
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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
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Publisher: |
Wiley Blackwell |
Saved in:
freely available
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