Abstract
We introduce a new estimation method for parametric intensity function models of inhomogeneous spatial point processes based on weighted estimating equations. The weights can incorporate information on both inhomogeneity and dependence of the process. Simulations show that significant efficiency gains can be achieved for non-Poisson processes, compared to the Poisson maximum likelihood estimator. An application to tropical forest data illustrates the use of the proposed method.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 867-880 |
| Number of pages | 14 |
| Journal | Biometrika |
| Volume | 97 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 1 2010 |
| Externally published | Yes |
Keywords
- Inhomogeneous spatial point process
- Intensity estimation
- Poisson maximum likelihood
- Weighted estimating equation
ASJC Scopus subject areas
- Statistics and Probability
- Mathematics(all)
- Agricultural and Biological Sciences (miscellaneous)
- Agricultural and Biological Sciences(all)
- Statistics, Probability and Uncertainty
- Applied Mathematics
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Cite this
Guan, Y., & Shen, Y. (2010). A weighted estimating equation approach for inhomogeneous spatial point processes. Biometrika, 97(4), 867-880. https://doi.org/10.1093/biomet/asq043