Skip to main content
Log in

Quermass-interaction process with convex compact grains

  • Published:
Applications of Mathematics Aims and scope Submit manuscript

Abstract

The paper concerns an extension of random disc Quermass-interaction process, i.e. the model of discs with mutual interactions, to the process of interacting objects of more general shapes. Based on the results for the random disc process and the process with polygonal grains, theoretical results for the generalized process are derived. Further, a simulation method, its advantages and the corresponding complications are described, and some examples are introduced. Finally, a short comparison to the random disc process is given.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H. Altendorf, F. Latourte, D. Jeulin, M. Faessel, L. Saintyant: 3D reconstruction of a multiscale microstructure by anisotropic tessellation models. Image Anal. Stereol. 33 (2014), 121–130.

    Article  Google Scholar 

  2. S. N. Chiu, D. Stoyan, W. S. Kendall, J. Mecke: Stochastic Geometry and Its Applications. Wiley Series in Probability and Statistics, John Wiley & Sons, Chichester, 2013.

    Book  MATH  Google Scholar 

  3. D. Dereudre: Existence of Quermass processes for non locally stable interaction and non bounded convex grains. Adv. Appl. Probab. 41 (2009), 664–681.

    Article  MathSciNet  MATH  Google Scholar 

  4. D. Dereudre, F. Lavaňcier, K. Stanková Helisová: Estimation of the intensity parameter of the germ-grain Quermass-interaction model when the number of germs is not observed. Scand. J. Stat. 41 (2014), 809–829.

    Article  MathSciNet  MATH  Google Scholar 

  5. P. J. Diggle: Binary mosaics and the spatial pattern of heather. Biometrics 37 (1981), 531–539.

    Article  Google Scholar 

  6. C. J. Geyer, J. Møller: Simulation procedures and likelihood inference for spatial point processes. Scand. J. Stat. 21 (1994), 359–373.

    MathSciNet  MATH  Google Scholar 

  7. K. Helisová: Modeling, statistical analyses and simulations of random items and behavior on material surfaces. Supplemental UE: TMS 2014 Conference Proceedings, San Diego, 2014, pp. 461–468.

    Google Scholar 

  8. P. Hermann, T. Mrkvicka, T. Mattfeldt, M. Minárová, K. Helisová, O. Nicolis, F. Wartner, M. Stehlík: Fractal and stochastic geometry inference for breast cancer: a case study with random fractal models and Quermass-interaction process. Stat. Med. 34 (2015), 2636–2661.

    Article  MathSciNet  Google Scholar 

  9. W. S. Kendall, M. N. M. van Lieshout, A. J. Baddeley: Quermass-interaction processes: conditions for stability. Adv. Appl. Probab. 31 (1999), 315–342.

    Article  MathSciNet  MATH  Google Scholar 

  10. M. Klazar: Generalised Davenport-Schinzel sequences: results, problems and applications. Integers: The Electronic Journal of Combinatorial Number Theory 2 (2002), A11.

    MathSciNet  MATH  Google Scholar 

  11. I. Molchanov: Theory of Random Sets. Probability and Its Applications, Springer, London, 2005.

    MATH  Google Scholar 

  12. J. Møller, K. Helisová: Power diagrams and interaction processes for unions of discs. Adv. Appl. Probab. 40 (2008), 321–347.

    Article  MathSciNet  MATH  Google Scholar 

  13. J. Møller, K. Helisová: Likelihood inference for unions of interacting discs. Scand. J. Stat. 37 (2010), 365–381.

    Article  MathSciNet  MATH  Google Scholar 

  14. J. Møller, R. P. Waagepetersen: Statistical Inference and Simulation for Spatial Point Processes. Monographs on Statistics and Applied Probability 100, Chapman and Hall/CRC, Boca Raton, 2004.

    MATH  Google Scholar 

  15. T. Mrkvička, T. Mattfeldt: Testing histological images of mammary tissues on compatibility with the Boolean model of random sets. Image Anal. Stereol. 30 (2011), 11–18.

    Article  MathSciNet  Google Scholar 

  16. T. Mrkvička, J. Rataj: On the estimation of intrinsic volume densities of stationary random closed sets. Stochastic Processes Appl. 118 (2008), 213–231.

    Article  MathSciNet  MATH  Google Scholar 

  17. J. Ohser, F. Mücklich: Statistical Analysis of Microstructures in Materials Science. Wiley Series in Statistics in Practice, Wiley, Chichester, 2000.

    MATH  Google Scholar 

  18. W. K. Pratt: Digital Image Processing. Wiley & Sons, New York, 2001.

    Book  MATH  Google Scholar 

  19. R Development Core Team: R: A language and environment for statistical computing. R Found Stat Comp, Vienna. http://www. R-project. org/, 2010.

    Google Scholar 

  20. K. Staňková Helisová, J. Staněk: Dimension reduction in extended Quermass-interaction process. Methodol. Comput. Appl. Probab. 16 (2014), 355–368.

    Article  MathSciNet  MATH  Google Scholar 

  21. M. Zikmundová, K. Staňková Helisová, V. Beneš: Spatio-temporal model for a random set given by a union of interacting discs. Methodol. Comput. Appl. Probab. 14 (2012), 883–894.

    Article  MathSciNet  MATH  Google Scholar 

  22. M. Zikmundová, K. Staňková Helisová, V. Beneš: On the use of particle Markov chain Monte Carlo in parameter estimation of space-time interacting discs. Methodol. Comput. Appl. Probab. 16 (2014), 451–463.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kateřina Helisová.

Additional information

The research was supported by Czech Science Foundation, grant No. 13-05466P.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Helisová, K., Staněk, J. Quermass-interaction process with convex compact grains. Appl Math 61, 463–487 (2016). https://doi.org/10.1007/s10492-016-0142-x

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10492-016-0142-x

Keywords

MSC 2010

Navigation