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Full Description
This book provides a comprehensive introduction to STIT tessellations, a class of random tessellations characterized by their stability under the iteration of tessellations. Emerging from a stochastic process of successive subdivisions of polytopes in Euclidean space, this model lends itself to a rigorous theoretical analysis.
Beyond their theoretical significance, STIT tessellations serve as valuable reference models for real-world applications — ranging from crack formation in materials science and fragmentation processes in geology to the subdivision of high-dimensional data sets in machine learning and the analysis of spatial patterns in communication systems.
Divided into four parts, this volume systematically explores the construction and analysis of tessellation-valued stochastic processes, emphasizing the interplay between geometric concepts and probabilistic methods. It positions STIT tessellations alongside classical models such as Poisson hyperplane and Poisson-Voronoi tessellations.
With its rigorous yet accessible approach, this book is an indispensable resource for researchers and practitioners in stochastic geometry, spatial modelling, and applied mathematics.



