Conditional simulation in dynamic linear models for spatial and temporal predictions of diffusive phenomena

Tonio Di Battista (), Lara Fontanella () and Luigi Ippoliti ()
Additional contact information
Tonio Di Battista: Universitá degli Studi “G. d’Annunzio”
Lara Fontanella: Universitá degli Studi “G. d’Annunzio”
Luigi Ippoliti: Universitá degli Studi “G. d’Annunzio”

Statistical Methods & Applications, 2004, vol. 12, issue 3, No 7, 375 pages

Abstract: Abstract. A spatial time series framework is used for stochastic modelling of daily average Sulphur Dioxide (SO2) levels in the Milan district. Within a spatio-temporal Kalman filter algorithm, stochastic conditional simulation is performed to obtain spatial and temporal predictions of the observed process. Unlike other recent space-time Kalman filters, the inclusion of a point source trend model also allows the development of a spatio-temporal state-space model that achieves dimension reduction in the analysis of large data set.

Keywords: Conditional simulation; Kalman filter; point source model; space-time modelling (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10260-003-0065-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:stmapp:v:12:y:2004:i:3:d:10.1007_s10260-003-0065-z

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2

DOI: 10.1007/s10260-003-0065-z

Access Statistics for this article

Statistical Methods & Applications is currently edited by Tommaso Proietti

More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().