Stochastic Geometry, Spatial Statistics and Random Fields Models and Algorithms

Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. Thi...

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Bibliographic Details
Other Authors: Schmidt, Volker (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2015, 2015
Edition:1st ed. 2015
Series:Lecture Notes in Mathematics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Stein’s Method for Approximating Complex Distributions, with a View towards Point Processes
  • Clustering Comparison of Point Processes, with Applications to Random Geometric Models
  • Random Tessellations and their Application to the Modelling of Cellular Materials
  • Stochastic 3D Models for the Micro-structure of Advanced Functional Materials
  • Boolean Random Functions
  • Random Marked Sets and Dimension Reduction
  • Space-Time Models in Stochastic Geometry
  • Rotational Integral Geometry and Local Stereology - with a View to Image Analysis
  • An Introduction to Functional Data Analysis
  • Some Statistical Methods in Genetics
  • Extrapolation of Stationary Random Fields
  • Spatial Process Simulation
  • Introduction to Coupling-from-the-Past using R
  • References.-Index