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Theory of Probability and Mathematical Statistics
Theory of Probability and Mathematical Statistics
ISSN 1547-7363(online) ISSN 0094-9000(print)

 

Modelling log Gaussian Cox processes with a given reliability and accuracy


Authors: Yu. V. Kozachenko and O. O. Pogorilyak
Translated by: N. Semenov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 76 (2007).
Journal: Theor. Probability and Math. Statist. 76 (2008), 77-91
MSC (2000): Primary 68U20; Secondary 60G10
Published electronically: July 14, 2008
MathSciNet review: 2368741
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Abstract | References | Similar Articles | Additional Information

Abstract: We consider stochastic Cox processes governed by a random intensity. Namely we consider the case where the logarithm of intensity is a separable stationary Gaussian stochastic process. We construct models approximating log Gaussian Cox processes with a given reliability and accuracy.


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Additional Information

Yu. V. Kozachenko
Affiliation: Department of Probability Theory and Mathematical Statistics, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email: yvk@univ.kiev.ua

O. O. Pogorilyak
Affiliation: Department of Probability Theory and Mathematical Statistics, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email: alex_pogorilyak@ukr.net

DOI: http://dx.doi.org/10.1090/S0094-9000-08-00733-3
PII: S 0094-9000(08)00733-3
Keywords: Log Gaussian Cox processes, random intensity, modelling, accuracy, reliability
Received by editor(s): February 23, 2006
Published electronically: July 14, 2008
Article copyright: © Copyright 2008 American Mathematical Society