TY  - JOUR
AU  - lara, Fontanella 
AU  - mariagrazia, Granturco 
PY  - 2005
TI  - Parsimonious Var Models For Air Pollution Dynamic Analysis
JF  - Journal of Mathematics and Statistics
VL  - 1
IS  - 4
DO  - 10.3844/jmssp.2005.267.276
UR  - https://thescipub.com/abstract/jmssp.2005.267.276
AB  - We discuss a framework to obtain temporal predictions for an evolving spatial field regularly sampled in time at arbitrary spatial locations. Difficulties caused by large data sets and the modelling of complicated spatio-temporal interactions limit the effectiveness of traditional space-time statistical models. In this study, we propose the use of a flexible approach to deal with large and small time-scale variability of the observed data. The temporal model is applied with respect to both the observed data domain and the common component domain, to achieve a dimensionality reduction.