UID:
almahu_9947363758902882
Format:
XXIV, 464 p. 133 illus., 63 illus. in color.
,
online resource.
ISBN:
9783319100647
Series Statement:
Lecture Notes in Mathematics, 2120
Content:
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.
Note:
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.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9783319100630
Language:
English
Subjects:
Mathematics
Keywords:
Aufsatzsammlung
;
Konferenzschrift
DOI:
10.1007/978-3-319-10064-7
URL:
http://dx.doi.org/10.1007/978-3-319-10064-7
URL:
Volltext
(lizenzpflichtig)
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