Source: Bernoulli Volume 15, Number 4
(2009), 1222-1242.
Many real phenomena may be modelled as random closed sets in ℝd, of different Hausdorff dimensions. In many real applications, such as fiber processes and n-facets of random tessellations of dimension n≤d in spaces of dimension d≥1, several problems are related to the estimation of such mean densities. In order to confront such problems in the general setting of spatially inhomogeneous processes, we suggest and analyze an approximation of mean densities for sufficiently regular random closed sets. We show how some known results in literature follow as particular cases. A series of examples throughout the paper are provided to illustrate various relevant situations.
References
[1] Ambrosio, L., Fusco, N. and Pallara, D. (2000). Functions of Bounded Variation and Free Discontinuity Problems. Oxford: Clarendon Press.
[2] Baddeley, A.J. and Molchanov, I.S. (1997). On the expected measure of a random set. In Proceedings of the International Symposium on Advances in Theory and Applications of Random Sets (Fontainebleau, 1996) 3–20. River Edge, NJ: World Scientific.
[3] Beneš, V. and Rataj, J. (2004). Stochastic Geometry: Selected Topics. Boston: Kluwer.
[4] Capasso, V. (ed.) (2003). Mathematical Modelling for Polymer Processing. Polymerization, Crystallization, Manufacturing. Springer Series on Mathematics in Industry 2. Heidelberg: Springer-Verlag.
[5] Capasso, V. and Micheletti, A. (2005). Stochastic geometry and related statistical problems in biomedicine. In Complex Systems in Biomedicine (A. Quarteroni et al., eds.). Milano: Springer.
[6] Capasso, V. and Villa, E. (2007). On mean densities of inhomogeneous geometric processes arising in material science and medicine. Image Anal. Stereol. 26 23–36.
[7] Capasso, V. and Villa, E. (2008). On the geometric densities of random closed sets. Stoch. Anal. Appl. 26 784–808.
[8] Carmeliet, P. and Jain, R.K. (2000). Angiogenesis in cancer and other diseases. Nature 407 249–257.
[9] Daley, D.J. and Vere-Jones, D. (1998). An Introduction to the Theory of Point Processes. New York: Springer.
Mathematical Reviews (MathSciNet):
MR950166
[10] Devroye, L. (1987). A Course in Density Estimation. Boston: Birkhauser Verlag.
Mathematical Reviews (MathSciNet):
MR891874
[11] Evans, L.C. and Gariepy, R.F. (1992). Measure Theory and Fine Properties of Functions. Boca Raton: CRC Press.
[12] Hahn, U., Micheletti, A., Pohlink, R., Stoyan, D. and Wendrock, H. (1999). Stereological analysis and modeling of gradient structures. J. Microsc. 195 113–124.
[13] Jeulin, D. (2002). Modelling random media. Image Anal. Stereol. 21 (Suppl. 1) S31–S40.
[14] Kärkkäinen, S., Jensen, E.B.V. and Jeulin, D. (2002). On the orientational analysis of planar fibre systems from digital images. J. Microsc. 207 69–77.
[15] Kolmogorov, A.N. (1956). Foundations of the Theory of Probability, 2nd English ed. New York: Chelsea.
Mathematical Reviews (MathSciNet):
MR79843
[16] Matheron, G. (1975). Random Sets and Integral Geometry. New York: Wiley.
Mathematical Reviews (MathSciNet):
MR385969
[17] Miles, R.E. and Serra, J. (eds.) (1978). Geometrical Probability and Biological Structures: Buffon’s 200th Anniversary. Lecture Notes in Biomathematics 23. Berlin–New York: Springer-Verlag.
Mathematical Reviews (MathSciNet):
MR518158
[18] Møller, J. (1992). Random Johnson–Mehl tessellations. Adv. in Appl. Probab. 24 814–844.
[19] Møller, J. (1994). Lectures on Random Voronoi Tessellations. Lecture Notes in Statistics 87. New York–Berlin–Heidelberg: Springer-Verlag.
[20] Pestman, W.R. (1998). Mathematical Statistics: An Introduction. Berlin: de Gruyter.
[21] Robbins, H.E. (1944). On the measure of a random set. Ann. Math. Statist. 15 70–74.
Mathematical Reviews (MathSciNet):
MR10347
[22] Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. London: Chapman & Hall.
Mathematical Reviews (MathSciNet):
MR848134
[23] Serra, J. (1984). Image Analysis and Mathematical Morphology. London: Academic Press.
Mathematical Reviews (MathSciNet):
MR753649
[24] Stoyan, D., Kendall, W.S. and Mecke, J. (1995). Stochastic Geometry and Its Applications. Chichester: Wiley.
Mathematical Reviews (MathSciNet):
MR895588
[25] Villa, E. (2007). Methods of geometric measure theory in stochastic geometry. Ph.D. thesis, University of Milan, Milan.
[26] Zähle, M. (1982). Random processes of Hausdorff rectifiable closed sets. Math. Nachr. 108 49–72.
Mathematical Reviews (MathSciNet):
MR695116