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024 7 $a10.1007/978-3-319-10064-7
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035   $a(DE-He213)978-3-319-10064-7
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100   $a20141024d2015      u|             0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aStochastic Geometry, Spatial Statistics and Random Fields$b[electronic resource] $eModels and Algorithms /$fedited by Volker Schmidt
205   $a1st ed. 2015.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015.
215   $a1 online resource (XXIV, 464 p. 133 illus., 63 illus. in color.)
225 1 $aLecture Notes in Mathematics,$x0075-8434 ;$v2120
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-319-10063-7 
327   $aStein?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.
330   $aProviding a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
410  0$aLecture Notes in Mathematics,$x0075-8434 ;$v2120
606   $aProbabilities
606   $aMathematical models
606   $aAlgorithms
606   $aGeometry
606   $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004
606   $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068
606   $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018
606   $aGeometry$3https://scigraph.springernature.com/ontologies/product-market-codes/M21006
615  0$aProbabilities.
615  0$aMathematical models.
615  0$aAlgorithms.
615  0$aGeometry.
615 14$aProbability Theory and Stochastic Processes.
615 24$aMathematical Modeling and Industrial Mathematics.
615 24$aAlgorithms.
615 24$aGeometry.
676   $a519.2
702   $aSchmidt$b Volker$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996213651603316
996   $aStochastic geometry, spatial statistics and random fields$9836596
997   $aUNISA