Constructing first order stationary autoregressive models via latent processes

Pitt, Michael K. and Chatfield, Chris and Walker, Stephen G. (2002) Constructing first order stationary autoregressive models via latent processes. Scandinavian Journal of Statistics, 29 (4). pp. 657-663. ISSN 0303-6898. (doi:https://doi.org/10.1111/1467-9469.00311) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1111/1467-9469.00311

Abstract

First order stationary autoregressive (AR(1)) models are introduced for which there exists a linear relation between the expectations of the observations, and where it is readily possible to arrange the marginal distributions to be other than normal.

Item Type: Article
Uncontrolled keywords: autocorrelation function; autoregressive process; EM algorithm; exponential family; latent process; stationary time series
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 25 Oct 2008 17:29 UTC
Last Modified: 06 May 2014 10:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/10569 (The current URI for this page, for reference purposes)
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