Statistics Seminar
| Date/Time: | Monday, 18 Nov 2013 from 4:10 pm to 5:00 pm |
|---|---|
| Location: | Snedecor 3105 |
| Cost: | Free |
| URL: | www.stat.iastate.edu |
| Contact: | Jeanette La Grange |
| Phone: | 515-294-3440 |
| Channel: | College of Liberal Arts and Sciences |
| Categories: | Lectures |
| Actions: | Download iCal/vCal | Email Reminder |
Space-time data sets are often collected at monitored discrete time lags, which are normally viewed as a component of time series. Valid and practical covariance structures are needed to model these types of data sets in various disciplines, such as environmental science, climatology, and agriculture. We propose two classes of spatio-temporal functions whose discrete temporal margins are some celebrated autoregressive and moving average (ARMA) models, and obtain necessary and sufficient conditions for them to be valid covariance functions. The possibility of taking advantage of well-established time series and spatial statistics tools makes it relatively easy to identify and fit the proposed model in practice. Moreover, those results are generalized to multivariate spatio-temporal setting to deal with the complex dependence structure among multiple attributes observed in continuous space and discrete time. A spatio-temporal model with moving average type of temporal marginis fitted to Kansas daily precipitation to illustrate the application of the proposed model comparing with some popular spatio-temporal models in literature.