Exponential family state space models based on a conjugate latent process

P. Vidoni

Journal of the Royal Statistical Society Series B, 1999, vol. 61, issue 1, 213-221

Abstract: This paper introduces non‐linear and non‐Gaussian state space models with analytic updating recursions for filtering and prediction. This new class of models involves some well‐known results in the theory of exponential models and of exponential dispersion models and the latent process is defined in such a way that both the filtering and the prediction distributions turn out to be conjugate to the observation distribution at each step. The corresponding analytic and inferential properties are investigated and some simple examples are presented.

Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1111/1467-9868.00172

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssb:v:61:y:1999:i:1:p:213-221

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9868

Access Statistics for this article

Journal of the Royal Statistical Society Series B is currently edited by P. Fryzlewicz and I. Van Keilegom

More articles in Journal of the Royal Statistical Society Series B from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().