On the construction of stationary AR(1) models via random distributions

Contreras-Cristan, A. and Mena, R.H. and Walker, S.G. (2009) On the construction of stationary AR(1) models via random distributions. Statistics, 43 (3). pp. 227-240. ISSN 0233-1888.

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Official URL
http://dx.doi.org/10.1080/02331880802259391

Abstract

We explore a method for constructing first-order stationary autoregressive-type models with given marginal distributions. We impose the underlying dependence structure in the model using Bayesian non-parametric predictive distributions. This approach allows for nonlinear dependency and at the same time works for any choice of marginal distribution. In particular, we look at the case of discrete-valued models; that is the marginal distributions are supported on the non-negative integers.

Item Type: Article
Uncontrolled keywords: AR model; Beta-Stacy process; Bayesian non-parametrics; discrete-valued time series; Plya trees; stationary process
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 17 Mar 2009 15:44
Last Modified: 07 Feb 2012 16:18
Resource URI: http://kar.kent.ac.uk/id/eprint/12680 (The current URI for this page, for reference purposes)
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