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Stochastic Geometry is the mathematical discipline which studies mathematical models for random geometric structures, as they appear frequently in almost all natural sciences or technical fields. Although its roots can be traced back to the 18th century (the Buffon needle problem), the modern theory of random sets was founded by D. Kendall and G. Matheron in the early 1970's. Its rapid development was influenced by applications in Spatial Statistics and by its close connections to Integral Geometry. The volume "Stochastic Geometry" contains the lectures given at the CIME summer school in Martina Franca in September 1974. The four main lecturers covered the areas of Spatial Statistics, Random Points, Integral Geometry and Random Sets, they are complemented by two additional contributions on Random Mosaics and Crystallization Processes. The book presents an up-to-date description of important parts of Stochastic Geometry.
Stochastic geometry --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Mathematics. --- Math --- Convex geometry. --- Discrete geometry. --- Differential geometry. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Convex and Discrete Geometry. --- Differential Geometry. --- Science --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Differential geometry --- Geometry --- Combinatorial geometry --- Distribution (Probability theory. --- Discrete groups. --- Global differential geometry. --- Geometry, Differential --- Groups, Discrete --- Infinite groups --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Discrete mathematics --- Convex geometry . --- Distribution. --- Stochastic geometry - Congresses
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This monograph is devoted to a completely new approach to geometric problems arising in the study of random fields. The groundbreaking material in Part III, for which the background is carefully prepared in Parts I and II, is of both theoretical and practical importance, and striking in the way in which problems arising in geometry and probability are beautifully intertwined. The three parts to the monograph are quite distinct. Part I presents a user-friendly yet comprehensive background to the general theory of Gaussian random fields, treating classical topics such as continuity and boundedness, entropy and majorizing measures, Borell and Slepian inequalities. Part II gives a quick review of geometry, both integral and Riemannian, to provide the reader with the material needed for Part III, and to give some new results and new proofs of known results along the way. Topics such as Crofton formulae, curvature measures for stratified manifolds, critical point theory, and tube formulae are covered. In fact, this is the only concise, self-contained treatment of all of the above topics, which are necessary for the study of random fields. The new approach in Part III is devoted to the geometry of excursion sets of random fields and the related Euler characteristic approach to extremal probabilities. "Random Fields and Geometry" will be useful for probabilists and statisticians, and for theoretical and applied mathematicians who wish to learn about new relationships between geometry and probability. It will be helpful for graduate students in a classroom setting, or for self-study. Finally, this text will serve as a basic reference for all those interested in the companion volume of the applications of the theory. These applications, to appear in a forthcoming volume, will cover areas as widespread as brain imaging, physical oceanography, and astrophysics.
Mathematics. --- Probability Theory and Stochastic Processes. --- Statistics, general. --- Geometry. --- Mathematical Methods in Physics. --- Distribution (Probability theory). --- Mathematical physics. --- Statistics. --- Mathématiques --- Géométrie --- Distribution (Théorie des probabilités) --- Physique mathématique --- Statistique --- Global differential geometry. --- Random fields. --- Stochastic geometry. --- Random fields --- Global differential geometry --- Mathematical Statistics --- Mathematics --- Physical Sciences & Mathematics --- Fields, Random --- Probabilities. --- Physics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Euclid's Elements --- Math --- Science --- Geometry, Differential --- Stochastic processes --- Distribution (Probability theory. --- Physical mathematics --- Physics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Statistics .
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