The Annals of Probability

Levy Random Measures

Alan F. Karr

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Abstract

A Levy random measure is characterized by a conditional independence structure analogous to the Markov property. Here we introduce Levy random measures and present their basic properties. Preservation of the Levy property under transformations of random measures (e.g., change of variable, passage to a limit) and under transformations of the probability laws of random measures is investigated. One random measure is said to be a submeasure of a second random measure if its probability law is absolutely continuous with respect to that of the second. We show that if the second measure is a Levy random measure then the submeasure is Levy if and only if the Radon-Nikodym derivative satisfies a natural factorization condition. These results are applied to extend the theories of Gibbs states on bounded sets in $\mathbb{R}^\nu$ and $\mathbf{Z}^\nu$.

Article information

Source
Ann. Probab., Volume 6, Number 1 (1978), 57-71.

Dates
First available in Project Euclid: 19 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aop/1176995610

Digital Object Identifier
doi:10.1214/aop/1176995610

Mathematical Reviews number (MathSciNet)
MR455115

Zentralblatt MATH identifier
0374.60063

JSTOR
links.jstor.org

Subjects
Primary: 60G55: Point processes
Secondary: 60G30: Continuity and singularity of induced measures 60H99: None of the above, but in this section 60J99: None of the above, but in this section 60K35: Interacting random processes; statistical mechanics type models; percolation theory [See also 82B43, 82C43]

Keywords
Levy random measure Markov property conditional independence submeasure multiplicative functional Gibbs state Gibbs random measure Markov random field Poisson random measure

Citation

Karr, Alan F. Levy Random Measures. Ann. Probab. 6 (1978), no. 1, 57--71. doi:10.1214/aop/1176995610. https://projecteuclid.org/euclid.aop/1176995610


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Corrections

  • See Correction: Alan F. Karr. Note: Correction to "Levy Random Measures". Ann. Probab., Volume 7, Number 6 (1979), 1098--1098.