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Tree-based models for random distribution of mass

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Abstract

A mathematical model for distribution of mass ind-dimensional space, based upon randomly embedding random trees into space, is introduced and studied. The model is a variant of thesuper Brownian motion process studied by mathematicians. We present calculations relating to (i) the distribution of position of a typical mass element, (ii) moments of the center of mass, (iii) large-deviation behavior, and (iv) a recursive self-similarity property.

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References

  1. D. J. Aldous, A random tree model associated with random graphs,Random Structures Algorithms 1:383–402 (1990).

    Google Scholar 

  2. D. J. Aldous, The continuum random tree II: An overview, inStochastic Analysis, M. T. Barlow and N. H. Bingham, eds.(Cambridge University Press, Cambridge, 1991), pp. 23–70.

    Google Scholar 

  3. D. J. Aldous, The continuum random tree III,Ann. Prob. 21:248–289 (1993).

    Google Scholar 

  4. D. J. Aldous, Recursive self-similarity for random trees, random triangulations and Brownian excursion,Ann. Prob., to appear (1993).

  5. N. A. C. Cressie,Statistics for Spatial Data (Wiley, 1991).

  6. D. A. Dawson, I. Iscoe, and E. A. Perkins, Super-Brownian motion: Path properties and hitting probabilities,Prob. Theory Related Fields 83:1235–205 (1989).

    Google Scholar 

  7. D. A. Dawson and E. Perkins, Historical processes,Mem. Am. Math. Soc. 93(454) (1991).

    Google Scholar 

  8. A. Dembo and O. Zeitouni,Large Deviations and Applications (Jones and Bartlett, Boston, 1992).

    Google Scholar 

  9. E. B. Dynkin, Representation for functionals of superprocesses by multiple stochastic integrals, with applications to self-intersection local times, inColloque Paul Levy sur les Processes Stochastiques, Asterisque 157-158:147–171 (1988).

    Google Scholar 

  10. E. B. Dynkin, Branching particle systems and superprocesses,Ann. Prob. 19:1157–1194 (1991).

    Google Scholar 

  11. E. B. Dynkin, Path processes and historical superprocesses,Prob. Theory Related Fields 90:1–36 (1991).

    Google Scholar 

  12. E. B. Dynkin, A probabilistic approach to one class of nonlinear differential equations,Prob. Theory Related Fields 89:89–115 (1991).

    Google Scholar 

  13. S. N. Evans and E. Perkins, Measure-valued Markov branching processes conditioned on non-extinction,Israel J. Math. 71:329–337 (1990).

    Google Scholar 

  14. T. S. Ferguson, Prior distributions on spaces of probability measures,Ann. Stat. 2:615–629 (1974).

    Google Scholar 

  15. J.-F. Le Gall, Brownian excursions, trees and measure-valued branching processes,Ann. Prob. 19:1399–1439 (1991).

    Google Scholar 

  16. J.-F. Le Gall, The uniform random tree in a Brownian excursion,Prob. Theory Related Fields 96:369–384 (1993).

    Google Scholar 

  17. S. Graf, R. D. Mauldin, and S. C. Williams, The exact Hausdorff dimension in random recursive constructions,Mem. Am. Math. Soc. 71(381):1–121 (1988).

    Google Scholar 

  18. D. A. Griffin,Advanced Spatial Statistics (Kluwer, 1988).

  19. T. Hara and G. Slade, Critical behavior of self-avoiding walk in five or more dimensions,Bull. Am. Math. Soc. 25:417–423 (1991).

    Google Scholar 

  20. T. Hara and G. Slade, The number and size of branched polymers in high dimensions,J. Stat. Phys. 67:1009–1038 (1992).

    Google Scholar 

  21. T. Hara and G. Slade, On the upper critical dimension of lattice trees and lattice animals.J. Stat. Phys. 59:1469–1510 (1990).

    Google Scholar 

  22. I. Iscoe, Ergodic theory and a local occupation time for measure-valued critical branching Brownian motion,Stochastics 18:197–243 (1986).

    Google Scholar 

  23. I. Iscoe, A weighted occupation time for a class of measure-valued branching processes,Prob. Theory Related Fields 71:85–116 (1986).

    Google Scholar 

  24. W. Lavine, Some aspects of Polya tree distributions for statistical modelling,Ann. Stat. 20:1222–1235 (1992).

    Google Scholar 

  25. N. Madras and G. Slade,The Self-Avoiding Walk (Birkhauser, 1992).

  26. R. D. Mauldin, W. D. Sudderth, and S. C. Williams, Polya trees and random distributions,Ann. Stat. 20:1203–1221 (1992).

    Google Scholar 

  27. E. Perkins, Polar sets and multiple points for super-Brownian motion,Ann. Prob. 18:453–491 (1990).

    Google Scholar 

  28. B. W. Silverman,Density Estimation for Statistics and Data Analysis (Chapman and Hall, 1986).

  29. H. E. Stanley and N. Ostrowsky, eds.,On Growth and Form: Fractal and Non-Fractal Patterns in Physics (NATO ASI Series E, Applied Science No. 100, Nijhoff, Dordrecht, 1986).

    Google Scholar 

  30. T. Vicsek,Fractal Growth Phenomena, 2nd ed. (World Scientific, Singapore, 1992).

    Google Scholar 

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Aldous, D. Tree-based models for random distribution of mass. J Stat Phys 73, 625–641 (1993). https://doi.org/10.1007/BF01054343

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  • DOI: https://doi.org/10.1007/BF01054343

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