Stochastic Geometry, Spatial Statistics and Random Fields, 2015 Models and Algorithms Lecture Notes in Mathematics Series, Vol. 2120
Coordonnateur : Schmidt Volker
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.
Frontier theoretical work on point processes, random fields and integral geometry
Extensive applications in materials science, biology and genetics
Extensive codes in Matlab and R that help the reader with applications
Many examples help the reader to deepen their understanding
Date de parution : 11-2014
Ouvrage de 464 p.
15.5x23.5 cm
Thèmes de Stochastic Geometry, Spatial Statistics and Random Fields :
Mots-clés :
60D05, 60G55, 60G60, 62H11, 62M40, 62P30, 62P10, Mathematical Models, Random Fields, Simulation Algorithms, Spatial Statistics, Stochastic Geometry