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Faà di Bruno's formula and spatial cluster modelling

Faà di Bruno's formula and spatial cluster modelling
Faà di Bruno's formula and spatial cluster modelling
The probability generating functional (p.g.fl.) provides a useful means of compactly representing point process models. Cluster processes can be described through the composition of p.g.fl.s, and factorial moment measures and Janossy measures can be recovered from the p.g.fl. using variational derivatives. This article describes the application of a recent result in variational calculus, a generalisation of Faà di Bruno’s formula, to determine such results for cluster processes.
2211-6753
109-117
Clark, Daniel E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Houssineau, Jeremie
54d4df9b-ceaa-456d-b668-63c617e6894a
Clark, Daniel E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Houssineau, Jeremie
54d4df9b-ceaa-456d-b668-63c617e6894a

Clark, Daniel E. and Houssineau, Jeremie (2013) Faà di Bruno's formula and spatial cluster modelling. Spatial Statistics, 6 (11), 109-117. (doi:10.1016/j.spasta.2013.09.002).

Record type: Article

Abstract

The probability generating functional (p.g.fl.) provides a useful means of compactly representing point process models. Cluster processes can be described through the composition of p.g.fl.s, and factorial moment measures and Janossy measures can be recovered from the p.g.fl. using variational derivatives. This article describes the application of a recent result in variational calculus, a generalisation of Faà di Bruno’s formula, to determine such results for cluster processes.

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e-pub ahead of print date: 16 October 2013
Published date: 1 November 2013
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Identifiers

Local EPrints ID: 474471
URI: http://eprints.soton.ac.uk/id/eprint/474471
DOI: doi:10.1016/j.spasta.2013.09.002
ISSN: 2211-6753
PURE UUID: ec5444a9-d963-43eb-8e03-8f97e2836f6f

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Date deposited: 22 Feb 2023 21:08
Last modified: 16 Mar 2024 23:15

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Contributors

Author: Daniel E. Clark
Author: Jeremie Houssineau

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