Partial-Likelihood Analysis of Spatio-Temporal Point-Process Data
Article first published online: 10 AUG 2009
© 2009, The International Biometric Society
Volume 66, Issue 2, pages 347–354, June 2010
How to Cite
Diggle, P. J., Kaimi, I. and Abellana, R. (2010), Partial-Likelihood Analysis of Spatio-Temporal Point-Process Data. Biometrics, 66: 347–354. doi: 10.1111/j.1541-0420.2009.01304.x
- Issue published online: 1 JUN 2010
- Article first published online: 10 AUG 2009
- Received May 2008. Revised February 2009. Accepted May 2009.
- Monte Carlo;
- Partial likelihood;
- Point process;
Summary We investigate the use of a partial likelihood for estimation of the parameters of interest in spatio-temporal point-process models. We identify an important distinction between spatially discrete and spatially continuous models. We focus our attention on the spatially continuous case, which has not previously been considered. We use an inhomogeneous Poisson process and an infectious disease process, for which maximum-likelihood estimation is tractable, to assess the relative efficiency of partial versus full likelihood, and to illustrate the relative ease of implementation of the former. We apply the partial-likelihood method to a study of the nesting pattern of common terns in the Ebro Delta Natural Park, Spain.