1996•Advances in Applied ProbabilityRequires access

Conditional simulation of a Boolean model

Christian Lantuéjoul

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Abstract

A Boolean model in ℝ d is the union of independent random compact subsets of ℝ d (called ‘grains’) located according to a Poisson point process. A sequential algorithm is proposed to conditionally simulate a Boolean model, i.e. so that a finite set of specified points belongs to the grains and another set to the complementary phase (referred to as the ‘pores’).

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What this paper is about

A Boolean model in ℝ d is the union of independent random compact subsets of ℝ d (called ‘grains’) located according to a Poisson point process. A sequential algorithm is proposed to conditionally simulate a Boolean model, i.e. so that a finite set of specified points belongs to the grains and another set to the complementary phase (referred to as the ‘pores’).

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Available abstract

A Boolean model in ℝ d is the union of independent random compact subsets of ℝ d (called ‘grains’) located according to a Poisson point process. A sequential algorithm is proposed to conditionally simulate a Boolean model, i.e. so that a finite set of specified points belongs to the grains and another set to the complementary phase (referred to as the ‘pores’).

Key concepts: Boolean model, Mathematics, Standard Boolean model, Set (abstract data type), Discrete mathematics, Point process, Point (geometry), Poisson distribution

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