000			01970 a2200277 4500
008			240919b1996 |||||||| |||| 001 0 eng d
020			_a9780521062503 (PB)
041			_aeng
080			_a519.21 _bMEE
100			_aMeester, Ronald
245			_aContinuum percolation
260			_bCambridge University Press _c1996 _aNew York
300			_ax, 238p.
490			_aCambridge tracts in mathematics _v119
504			_aIncludes bibliography and index in (233-238)p.
505			_a1 - Introduction, 2 - Basic methods, 3 - Occupancy in Poisson Boolean models, 4 - Vacancy in Poisson Boolean models, 5 - Distinguishing features of the Poisson Boolean model, 6 - The Poisson random-connection model, 7 - Models driven by general processes, 8 - Other continuum percolation models,
520			_aMany phenomena in physics, chemistry, and biology can be modelled by spatial random processes. One such process is continuum percolation, which is used when the phenomenon being modelled is made up of individual events that overlap, for example, the way individual raindrops eventually make the ground evenly wet. This is a systematic rigorous account of continuum percolation. Two models, the Boolean model and the random connection model, are treated in detail, and related continuum models are discussed. All important techniques and methods are explained and applied to obtain results on the existence of phase transitions, equality and continuity of critical densities, compressions, rarefaction, and other aspects of continuum models. This self-contained treatment, assuming only familiarity with measure theory and basic probability theory, will appeal to students and researchers in probability and stochastic geometry.
650			_aProbability
650			_aPercolation
650			_aStochastic processes
650			_aBoolean models
650			_aContinuum percolation models
690			_aMathematics
700			_aRoy, Rahul
942			_cBK
999			_c60553 _d60553