Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms
This volume is an attempt to provide a graduate level introduction to various aspects of shastic 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 shastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.
1119986714
Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms
This volume is an attempt to provide a graduate level introduction to various aspects of shastic 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 shastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.
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Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms

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

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

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

Overview

This volume is an attempt to provide a graduate level introduction to various aspects of shastic 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 shastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.

Product Details

ISBN-13: 9783319100630
Publisher: Springer International Publishing
Publication date: 10/24/2014
Series: Lecture Notes in Mathematics , #2120
Edition description: 2015
Pages: 464
Product dimensions: 6.10(w) x 9.25(h) x (d)

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.- Shastic 3D Models for the Micro-structure of Advanced Functional Materials.- Boolean Random Functions.- Random Marked Sets and Dimension Reduction.- Space-Time Models in Shastic 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.

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