EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 17 (2013) ESAIM: PS, 17 (2013) 767-788 References
Free Access
Issue
ESAIM: PS
Volume 17, 2013
Page(s) 767 - 788
DOI https://doi.org/10.1051/ps/2012027
Published online 04 November 2013
  1. A.J. Baddeley, M. Kerscher, K. Schladitz and B.T. Scott, Estimating the J function without edge correction. Research report of the department of mathematics, University of Western Australia (1997). [Google Scholar]
  2. J-M. Bardet, P. Doukhan, G. Lang and N. Ragache, Dependent Lindeberg central limit theorem and some applications. ESAIM: PS 12 (2008) 154–172. [CrossRef] [EDP Sciences] [Google Scholar]
  3. S. Bernstein, Quelques remarques sur le théorème limite Liapounoff. C.R. (Dokl.) Acad. Sci. URSS 24 (1939) 3–8. [Google Scholar]
  4. J.E. Besag, Comments on Ripley’s paper. J. Roy. Statist. Soc. Ser. B 39 (1977) 193–195. [Google Scholar]
  5. S.N. Chiu, Correction to Koen’s critical values in testing spatial randomness. J. Stat. Comput. Simul. 77 (2007) 1001–1004. [Google Scholar]
  6. S.N. Chiu and K.I. Liu, Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions. Comput. Stat. Data Anal. 53 (2009) 3817–3834. [Google Scholar]
  7. N.A. Cressie, Statistics for spatial data. John Wiley and Sons, New York (1993). [Google Scholar]
  8. P.J. Diggle, Statistical analysis of spatial point patterns. Academic Press, London (1983). [Google Scholar]
  9. M. Fromont, B. Laurent and P. Reynaud-Bouret, Adaptive tests of homogeneity for a Poisson process. Ann. I.H.P. (B) 47 (2011) 176–213. [Google Scholar]
  10. P. Grabarnik and S.N. Chiu, Goodness-of-fit test for complete spatial randomness against mixtures of regular and clustured spatial point processes. Biometrika 89 (2002) 411–421. [Google Scholar]
  11. J. Gignoux, C. Duby and S. Barot, Comparing the performances of Diggle’s tests of spatial randomness for small samples with and without edge effect correction: application to ecological data. Biometrics 55 (1999) 156–164. [Google Scholar]
  12. Y. Guan, On nonparametric variance estimation for second-order statistics of inhomogeneous spatial point Processes with a known parametric intensity form. J. Am. Stat. Ass. 104 (2009) 1482–1491. [CrossRef] [Google Scholar]
  13. L.P. Ho and S.N. Chiu, Testing Uniformity of a Spatial Point Pattern. J. Comput. Graph. Stat. 16 2 (2007) 378–398. [Google Scholar]
  14. L. Heinrich, Goodness-of-fit tests for the second moment function of a stationary multidimensional Poisson process. Statistics 22 (1991) 245–268. [Google Scholar]
  15. J. Illian, A. Penttinen, H. Stoyan and D. Stoyan, Statistical analysis and modelling of spatial point patterns. Wiley-Interscience, Chichester (2008). [Google Scholar]
  16. C. Koen, Approximate confidence bounds for Ripley’s statistic for random points in a square. Biom. J. 33 (1991) 173–177. [Google Scholar]
  17. E. Marcon and F. Puech, Evaluating the geographic concentration of industries using distance-based methods. J. Econom. Geogr. 3 (2003) 409–428. [CrossRef] [Google Scholar]
  18. J. Møller and R.P. Waagepetersen, Statistical inference and simulation for spatial point processes, vol. 100 of Monographs on statistics and applied probability. Chapman and Hall/CRC, Boca Raton (2004). [Google Scholar]
  19. R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. http://www.R-project.org. [Google Scholar]
  20. B.D. Ripley, The second-order analysis of stationary point processes. J. Appl. Probab. 13 (1976) 255–266. [Google Scholar]
  21. B.D. Ripley, Modelling spatial patterns. J. Roy. Statist. Soc. Ser. B 39 2 (1977) 172–212. [Google Scholar]
  22. B.D. Ripley, Tests of randomness for spatial point patterns. J. Roy. Statist. Soc. Ser. B 41 3 (1979) 368–374. [Google Scholar]
  23. B.D. Ripley, Spatial statistics. John Wiley and Sons, New York (1981). [Google Scholar]
  24. R. Saunders and G.M. Funk, Poisson limits for a clustering model of Strauss. J. Appl. Probab. 14 (1977) 776–784. [Google Scholar]
  25. D. Stoyan, W.S. Kendall and J. Mecke, Stochastic geometry and its applications. Akademie-Verlag, Berlin (1987). [Google Scholar]
  26. D. Stoyan and H. Stoyan, Fractals, Random Shapes and Point Fields. Methods of Geometrical Statistics. John Wiley and Sons, New York (1994). [Google Scholar]
  27. C.C. Taylor, I.L. Dryden and R. Farnoosh, The K function for nearly regular point processes. Biometrics 57 (2000) 224–231. [Google Scholar]
  28. M. Thomas, A generalization of Poisson’s binomial limit for use in ecology. Biometrika 36 (1949) 18–25. [MathSciNet] [PubMed] [Google Scholar]
  29. E. Thönnes and M.-C. van Lieshout, A comparative study on the power of van Lieshout and Baddeley’s J function. Biom. J. 41 (1999) 721–734. [Google Scholar]
  30. J.S. Ward and F.J. Ferrandino, New derivation reduces bias and increases power of Ripley’s L index. Ecological Modelling 116 (1999) 225–236. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.