Gibbs and autoregressive Markov processes

Nieto-Barajas, Luis E. and Walker, Stephen G. (2007) Gibbs and autoregressive Markov processes. Statistics and Probability Letters, 77 (14). pp. 1479-1485. ISSN 0167-7152. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1016/j.spl.2007.02.015

Abstract

In this paper we show that particular Gibbs sampler Markov processes can be modified to an autoregressive Markov process. The procedure allows the easy derivation of the innovation variables which provide strictly stationary autoregressive processes with fixed marginals. In particular, we provide the innovation variables for beta, gamma and Dirichlet processes.

Item Type: Article
Uncontrolled keywords: autoregressive process; cadlag functions space; continuous time Markov process; discrete time Markov process; Levy process
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Suzanne Duffy
Date Deposited: 21 Apr 2008 08:13
Last Modified: 25 Jun 2014 10:43
Resource URI: http://kar.kent.ac.uk/id/eprint/2663 (The current URI for this page, for reference purposes)
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