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Sparse Sampling and Maximum Likelihood Estimation for Boolean Models
Author(s) -
Ayala G.,
Ferrandiz J. R.,
Montes F.
Publication year - 1991
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710330215
Subject(s) - independence (probability theory) , mathematics , sampling (signal processing) , boolean model , maximum likelihood , algorithm , statistics , computer science , filter (signal processing) , computer vision
A condition for practical independence of contact distribution functions in Boolean models is obtained. This result allows the authors to use maximum likelihcod methods, via sparse sampling, for estimating unknown parameters of an isotropic Boolean model. The second part of this paper is devoted to a simulation study of the proposed method. AMS classification: 60D05