Math 2.0

Probability theory and stochastic processes Definition

Boolean model

Builds on Poisson point processCompact setIndependent and identically distributed random variablesClosed ball

Definition

Let d≥1d \ge 1 and λ>0\lambda > 0. Let Φ={x1,x2,…}\Phi = \set{x_1, x_2, \ldots} be a homogeneous Poisson point process in ℝd\R^d with intensity λ\lambda; its points are the germs. Let K1,K2,…K_1, K_2, \ldots be independent and identically distributed random nonempty compact sets in ℝd\R^d, independent of Φ\Phi; they are the grains. Let KK denote a random set with their common law. Let VdV_d be Lebesgue measure on ℝd\R^d, and let BB be the closed unit ball centred at 00. Assume E[Vd(K+B)]<∞E[V_d(K + B)] < \infty, where K+B={k+b:k∈K,b∈B}K + B = \set{k + b : k \in K, b \in B}. The Boolean model with these germs and grains is the random set Ξ=⋃i≥1(xi+Ki).\Xi = \bigcup_{i \ge 1} (x_i + K_i).

Remarks

Under the integrability assumption, only finitely many grains xi+Kix_i + K_i meet each bounded set almost surely, so Ξ\Xi is a random closed set. Its law is invariant under translations of ℝd\R^d.

Example: let d=2d = 2 and let every grain be the closed disc of radius r>0r > 0 centred at 00. Then V2(K+B)=π(r+1)2V_2(K + B) = \pi (r + 1)^2 is finite, so the assumption holds. A point yy is uncovered exactly when Φ\Phi has no point in the disc of radius rr around yy, which has probability e−λπr2e^{-\lambda \pi r^2}. So the covered fraction of the plane is p=1−e−λπr2p = 1 - e^{-\lambda \pi r^2}. In general, P(y∈Ξ)=1−e−λE[Vd(K)]P(y \in \Xi) = 1 - e^{-\lambda E[V_d(K)]} for every y∈ℝdy \in \R^d.

Non-example: put the same discs at the points of the lattice ℤ2\Z^2 instead of a Poisson process. The union is a union of discs, but the germs do not form a Poisson point process, so it is not a Boolean model.

The Boolean model is also called the Poisson germ-grain model.

Reading path

To understand this page from the ground up, read these 73 pages in order. The foundations come first.

  1. Construction of the reals from Cauchy sequences concept
  2. Element definition
  3. Factorial definition
  4. Independent and identically distributed random variables concept
  5. Integers object
  6. Ordered field definition
  7. Proposition concept
  8. Random experiment concept
  9. Rational numbers object
  10. Real numbers object
  11. Set definition
  12. Ring of integers statement
  13. Conjunction definition
  14. Disjunction definition
  15. Implication definition
  16. Predicate definition
  17. Empty set object
  18. Family of sets definition
  19. Ordered pair definition
  20. Intersection definition
  21. Union definition
  22. Sample space definition
  23. The rationals form a field statement
  24. Existential quantifier definition
  25. Universal quantifier definition
  26. Cartesian product definition
  27. Subset definition
  28. Union of a family of sets definition
  29. The rationals form an ordered field statement
  30. Uniqueness quantifier definition
  31. Binary relation definition
  32. Universal set definition
  33. Power set definition
  34. Order on the reals definition
  35. Topological space definition
  36. Complement definition
  37. Function definition
  38. Subspace topology definition
  39. Interval definition
  40. Injective function definition
  41. Preimage of a set definition
  42. Sigma-algebra definition
  43. Metric space definition
  44. Countable set definition
  45. Event definition
  46. Closed ball definition
  47. Open ball definition
  48. Borel sigma-algebra definition
  49. Probability axioms concept
  50. Metric topology definition
  51. Probability measure definition
  52. Open set definition
  53. Open cover definition
  54. Probability distribution definition
  55. Probability space definition
  56. Compact space definition
  57. Conditional probability definition
  58. Random variable definition
  59. Compact set definition
  60. Discrete random variable definition
  61. Independence of two events definition
  62. Cumulative distribution function definition
  63. Stochastic process concept
  64. Random variable with a density definition
  65. Probability mass function definition
  66. Mutual independence of events definition
  67. Probability density function definition
  68. Poisson distribution definition
  69. Independent sigma-algebras definition
  70. Exponential distribution definition
  71. Independence of random variables definition
  72. Poisson point process definition
  73. Boolean model definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Boolean_model_(probability_theory)
About this page
Tag3PZ3TMW86C
URIm2://3PZ3TMW86C
Kinddefinition
WritingW0 stub
MSC60D05, 60G55
DefinesBoolean model
UsesPoisson point process, Compact set, Independent and identically distributed random variables, Closed ball
Changed2 November 2026

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