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

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Year of publication:	2005
Authors:	Mena, Ramsés H. ; Walker, Stephen G.
Publisher:	[S.l.] : SSRN
Subject:	Theorie \| Theory \| Nichtparametrisches Verfahren \| Nonparametric statistics \| Bayes-Statistik \| Bayesian inference \| Autokorrelation \| Autocorrelation

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Extent:	1 Online-Ressource (17 p)
Type of publication:	Book / Working Paper
Language:	English
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014061717