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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| Format: | eBook |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Series: | Lecture Notes in Mathematics,
2120 |
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| Online Access: | Click here to view the full text content |
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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.