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Constructing first order stationary autoregressive models via latent processes

Pitt, Michael K., Chatfield, Chris, 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: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) (KAR id:10569)

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.
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
DOI/Identification number: 10.1111/1467-9469.00311
Uncontrolled keywords: autocorrelation function; autoregressive process; EM algorithm; exponential family; latent process; stationary time series
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Judith Broom
Date Deposited: 25 Oct 2008 17:29 UTC
Last Modified: 16 Nov 2021 09:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/10569 (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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