Diggle, Peter J. and Brix, Anders (2001) Spatio-temporal prediction for log-Gaussian Cox processes. Journal of the Royal Statistical Society Series B (Statistical Methodology), 63 (4). pp. 823-841.
Full text not available from this repository.Official URL: http://dx.doi.org/10.1111/1467-9868.00315
Abstract
Space–time point pattern data have become more widely available as a result of technological developments in areas such as geographic information systems. We describe a flexible class of space–time point processes. Our models are Cox processes whose stochastic intensity is a space–time Ornstein–Uhlenbeck process. We develop moment-based methods of parameter estimation, show how to predict the underlying intensity by using a Markov chain Monte Carlo approach and illustrate the performance of our methods on a synthetic data set.
| Item Type: | Article |
|---|---|
| Journal or Publication Title: | Journal of the Royal Statistical Society Series B (Statistical Methodology) |
| Additional Information: | RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research |
| Subjects: | Q Science > QA Mathematics |
| Departments: | Faculty of Health and Medicine > Medicine VC's Office |
| ID Code: | 2412 |
| Deposited By: | ep_importer |
| Deposited On: | 31 Mar 2008 14:16 |
| Refereed?: | Yes |
| Published?: | Published |
| Last Modified: | 26 Jul 2012 16:21 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/2412 |
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