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Stochastic geometry, spatial statist...

Schmidt, Volker.

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Stochastic geometry, spatial statistics and random fields = models and algorithms /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic geometry, spatial statistics and random fields/ edited by Volker Schmidt.
Reminder of title:	models and algorithms /
other author:	Schmidt, Volker.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xxiv, 464 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Stochastic geometry - Congresses. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-10064-7
ISBN:	9783319100647 (electronic bk.)

Stochastic geometry, spatial statistics and random fields = models and algorithms /
Stochastic geometry, spatial statistics and random fieldsmodels and algorithms /[electronic resource] :edited by Volker Schmidt. - Cham :Springer International Publishing :2015. - xxiv, 464 p. :ill. (some col.), digital ;24 cm. - Lecture notes in mathematics,21200075-8434 ;. - Lecture notes in mathematics ;2046..

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.

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.

ISBN: 9783319100647 (electronic bk.)

Standard No.: 10.1007/978-3-319-10064-7doiSubjects--Topical Terms:

2109646
Stochastic geometry
--Congresses.

LC Class. No.: QA273.5

Dewey Class. No.: 519.2

Stochastic geometry, spatial statistics and random fields = models and algorithms /
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505 0 $a 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.
520 $a 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.
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