Spatial point process models of defensive strategies: Detecting changes

Statistical Inference for Stochastic Processes

Volumn 9, Issue 1, 2006, Pages 31-46

  Kornak, John ^a   Irwin, Mark E ^a   Cressie, Noel ^a  

^a OHIO STATE UNIVERSITY   (United States)

Author keywords

Conditional power; Geopolitical tendencies; Intensity function; Kernel smoothing; Monte Carlo testing; Poisson point process

Indexed keywords

EID: 33646536996     PISSN: 13870874     EISSN: 15729311     Source Type: Journal    
DOI: 10.1007/s11203-004-2894-2     Document Type: Article

References (19)

1. Allard, D. and Fraley, C.: Nonparametric maximum likelihood estimation of features in spatial point processes using Voronoi tessellation, J. Am. Stat. Assoc. 92 (1997), 1485-1493.
2. Alm, S. E.: On the distribution of scan statistics of a two-dimensional Poisson process, Adv. Appl. Probab. 29 (1997), 1-18.
3. Barnard, G.: Comment on 'The spectral analysis of point processes' by M. S. Bartlett. J. Royal Stat. Soc. B 25 (1963), 294.
4. Besag, J. E. and Diggle, P. J: Simple Monte Carlo tests for spatial pattern, Appl. Stat. 26 (1977), 327-333.
5. Birnbaum, Z. W.: Testing for intervals of increased mortality. In: Barlow, R. E., Fussell, J. B. and Singpurwalla, N. D. (eds), Reliability and Fault Tree Analysis, SIAM, Philadelphia, PA, 1975, 413-426.
6. Byers, S. and Raftery, A. E.: Nearest-neighbor clutter removal for estimating features in spatial point processes, J. Am. Stat. Assoc. 93 (1998), 577-584.
7. Chen, J. and Glaz, J.: Two-dimensional discrete scan statistics, Stat. Probab. Lett. 31 (1996), 59-68.
8. Cressie, N.: Statistics for Spatial Data, Revised Edition, Wiley, New York, 1993.
9. Dasgupta, A. and Raftery, A. E.: Detecting features in point processes with clutter via model-based clustering, J. Am. Stat. Assoc. 93 (1998), 294-302.
10. Friston, K. J.: Statistical parametric mapping. Book manuscript. Introductory chapter available at http://www.fil.ion.ucl.ac.uk/spm/papers/SPM- Chapter.pdf, 2002.
11. Glaz, J., Naus, J. I. and Wallenstein, S.: Scan Statistics, Springer-Verlag, New York, 2001.
12. Hope, A. C. A.: A simplified Monte Carlo significance test procedure, J. Royal Stat. Soc. B, 30 (1968), 582-598.
13. Kulldorff, M.: A spatial scan statistic. Communications in Statistics. Theory and Methods 26 (1997), 1481-1496.
14. Kulldorff, M. Spatial scan statistics, models, calculations, and applications, In: Glaz, J. and Balakrishnan. N. (eds.), Scan Statistics and Applications, Birkhauser, Boston, 1999.
15. Naus, J. I.: Clustering of random points in two dimensions, Biometrika 52 (1965), 263-267.
16. Priebe, C. E., Olson, T. and Healy, D. M. Jr: A spatial scan statistic for stochastic scan partitions, J. Am. Stat. Assoc. 92 (1997), 1476-1484.
17. Rosenfeld, A. and Kak, A. C.: Digital Picture Processing, Academic Press, New York, 1976.
18. Tubbs, R. N., Baldwin, J. E., Mackay, C. D. and Cox, G. C.: Diffraction-limited CCD imaging with faint reference stars, Astron. Astrophys. 387 (2002), L21-L24.
19. Turnbull, B. W., Iwano, E. J., Burnett, W. S., Howe, H. L. and Clark, L. C.: Monitoring for clusters of disease: application to leukemia incidence in upstate New York, Am. J. Epidemiol. 132 (1990), S136-S143.