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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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.
|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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