Asymptotic properties of estimators for parameters of the Boolean model

DOI10.2307/1427437zbMath0806.62078OpenAlexW2324773403MaRDI QIDQ4306628

Dietrich Stoyan, Ilya S. Molchanov

Publication date: 19 September 1994

Published in: Advances in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/1427437

zbMATH Keywords

asymptotic normalitycentral limit theoremCLTapproximation techniquekernel type estimatorspherical grainsasymptotically normally distributed estimatorarea fractionconvex grainsempirical radius distributionintensity of the lower positive tangent point processm-dependent fieldsmean perimeterspecific boundary lengthstationary Boolean modelstypical convex grain

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Geometric probability and stochastic geometry (60D05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (10)

Statistics for Poisson Models of Overlapping Spheres ⋮ Using two-point set statistics to estimate the diameter distribution in Boolean models with circular grains ⋮ Strong convergence of kernel estimators for product densities of absolutely regular point processes ⋮ Description of the symmetric convex random closed sets as zonotopes from their Feret diameters ⋮ Random Sets: Models and Statistics ⋮ Nonparametric and Parametric Estimation for a Linear Germination‐Growth Model ⋮ Regression models for Boolean random sets ⋮ Kernel estimation of the diameter distribution in boolean models with spherical grains ⋮ A Contribution to the Nonparametric Statistics of Particle Systems ⋮ A Contribution to the Nonparametric Statistics of Particle Systems

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