Models of stochastic geometry — A survey

This paper discusses some models of stochastic geometry which are of potential interest for operations research. These are the Boolean model, a certain model for random compact sets and marked point processes. The Boolean model is a generalization of the well-known queueing systemM/G/∞. The random compact set model may be useful for modelling spatial spreading processes such as fires, cancers or holes in the Earth's surface. Marked point processes are used here as models of forests and used for a statistical study of the spatial distribution of damaged trees.

[1]  B. D. Ripley,et al.  Statistical Inference for Spatial Processes: Preface , 1988 .

[2]  H. Robbins On the Measure of a Random Set , 1944 .

[3]  D. Saupe Algorithms for random fractals , 1988 .

[4]  An incomplete Voronoi tessellation , 1993 .

[5]  A consistent estimate of parameters of Boolean models of random closed sets , 1992 .

[6]  V. Schmidt,et al.  Queues and Point Processes , 1983 .

[7]  G. Matheron Random Sets and Integral Geometry , 1976 .

[8]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams , 1992, Wiley Series in Probability and Mathematical Statistics.

[9]  B. Ripley,et al.  Introduction to the Theory of Coverage Processes. , 1989 .

[10]  Dietrich Stoyan,et al.  Marked Point Processes in Forest Statistics , 1992, Forest Science.

[11]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[12]  I. Molchanov Handling with spatial censored observations in statistics of Boolean models of random sets , 1992 .

[13]  ASYMPTOTIC PROPERTIES OF STEREOLOGICAL ESTIMATORS OF VOLUME FRACTION FOR STATIONARY RANDOM SETS , 1982 .

[14]  Dietrich Stoyan,et al.  Fraktale, Formen, Punktfelder : Methoden der Geometrie-Statistik , 1992 .

[15]  R. Wets,et al.  On the Convergence in Distribution of Measurable Multifunctions Random Sets Normal Integrands, Stochastic Processes and Stochastic Infima , 1986 .

[16]  L. Santaló Integral geometry and geometric probability , 1976 .

[17]  J. Møller,et al.  Random Johnson-Mehl tessellations , 1992, Advances in Applied Probability.

[18]  R. A. Vitale An alternate formulation of mean value for random geometric figures * , 1988 .

[19]  Dietrich Stoyan,et al.  Trunk-top relations in a Siberian pine forest , 1993 .

[20]  Rick Durrett,et al.  Crabgrass, measles and gypsy moths: An introduction to modern probability , 1988 .

[21]  Dietrich Stoyan,et al.  Statistical analysis for a class of line segment processes , 1989 .

[22]  Zvi Artstein Weak Convergence of Set-Valued Functions and Control , 1975 .

[23]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[24]  Noel A Cressie,et al.  A spatial statistical analysis of tumor growth , 1992 .

[25]  I. Molchanov Random sets. A survey of results and applications , 1991 .

[26]  Michel Schmitt Estimation of the density in a stationary Boolean model , 1991 .

[27]  B. Ripley Statistical inference for spatial processes , 1990 .