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. ISSN 1369-7412
Full text not available from this repository.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.