A Mecke-type characterization of the Dirichlet–Ferguson measure
Dello Schiavo L, Lytvynov E. 2023. A Mecke-type characterization of the Dirichlet–Ferguson measure. Electronic Communications in Probability. 28, 1–12.
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Author
Dello Schiavo, LorenzoISTA 
;
Lytvynov, Eugene
;
Lytvynov, EugeneDepartment
Abstract
We prove a characterization of the Dirichlet–Ferguson measure over an arbitrary finite diffuse measure space. We provide an interpretation of this characterization in analogy with the Mecke identity for Poisson point processes.
Publishing Year
Date Published
2023-05-05
Journal Title
Electronic Communications in Probability
Acknowledgement
Research supported by the Sfb 1060 The Mathematics of Emergent Effects (University of Bonn). L.D.S. gratefully acknowledges funding of his current position by the Austrian Science Fund (FWF) through project ESPRIT 208.
Volume
28
Page
1-12
eISSN
IST-REx-ID
Cite this
Dello Schiavo L, Lytvynov E. A Mecke-type characterization of the Dirichlet–Ferguson measure. Electronic Communications in Probability. 2023;28:1-12. doi:10.1214/23-ECP528
Dello Schiavo, L., & Lytvynov, E. (2023). A Mecke-type characterization of the Dirichlet–Ferguson measure. Electronic Communications in Probability. Institute of Mathematical Statistics. https://doi.org/10.1214/23-ECP528
Dello Schiavo, Lorenzo, and Eugene Lytvynov. “A Mecke-Type Characterization of the Dirichlet–Ferguson Measure.” Electronic Communications in Probability. Institute of Mathematical Statistics, 2023. https://doi.org/10.1214/23-ECP528.
L. Dello Schiavo and E. Lytvynov, “A Mecke-type characterization of the Dirichlet–Ferguson measure,” Electronic Communications in Probability, vol. 28. Institute of Mathematical Statistics, pp. 1–12, 2023.
Dello Schiavo L, Lytvynov E. 2023. A Mecke-type characterization of the Dirichlet–Ferguson measure. Electronic Communications in Probability. 28, 1–12.
Dello Schiavo, Lorenzo, and Eugene Lytvynov. “A Mecke-Type Characterization of the Dirichlet–Ferguson Measure.” Electronic Communications in Probability, vol. 28, Institute of Mathematical Statistics, 2023, pp. 1–12, doi:10.1214/23-ECP528.
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