Title:	Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms		Volume:
Author(s):	Volker Schmidt (eds.)
Series:	Lecture Notes in Mathematics 2120	Periodical:
Publisher:	Springer International Publishing	City:
Year:	2015	Edition:
Language:	English	Pages:	XXIV, 464 p. 133 illus. 63 illus. in color.
ISBN:	978-3-319-10063-0, 978-3-319-10064-7	ID:	1292349
Time added:	2014-11-11 00:00:00	Time modified:	2014-12-27 02:40:11
Library:		Library issue:
Size:	14 MB (14709850 bytes)	Extension:	pdf
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. 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 regarded 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 : Content: 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