Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms

✍ Scribed by Schmidt, Volker H (eds.)

• Publisher: Springer Verlag
• Year: 2015
• Tongue: English
• Leaves: 484
• Series: Springer Lecture notes in mathematics 2120
• Category: Library

✦ Synopsis

This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods

✦ Table of Contents

Front Matter....Pages i-xxiv
Stein’s Method for Approximating Complex Distributions, with a View towards Point Processes....Pages 1-30
Clustering Comparison of Point Processes, with Applications to Random Geometric Models....Pages 31-71
Random Tessellations and their Application to the Modelling of Cellular Materials....Pages 73-93
Stochastic 3D Models for the Micro-structure of Advanced Functional Materials....Pages 95-141
Boolean Random Functions....Pages 143-169
Random Marked Sets and Dimension Reduction....Pages 171-203
Space-Time Models in Stochastic Geometry....Pages 205-232
Rotational Integral Geometry and Local Stereology - with a View to Image Analysis....Pages 233-255
An Introduction to Functional Data Analysis....Pages 257-292
Some Statistical Methods in Genetics....Pages 293-320
Extrapolation of Stationary Random Fields....Pages 321-368
Spatial Process Simulation....Pages 369-404
Introduction to Coupling-from-the-Past using R ....Pages 405-439
Back Matter....Pages 441-466