Classification of Points in Superpositions of Strauss and Poisson Processes
Journal article, 2015

Consider a realisation of a point process which is formed as a superposition of a regular point process, here a Strauss process, and some Poisson noise. The aim of the current work is to decide which of the two processes each point belongs to. We construct an MCMC algorithm which estimates the parameters of the superposition model and obtains posterior probabilities for each point of being a Strauss point. The algorithm is evaluated in a simulation study. Finally, it is applied to our motivating data set containing the locations of air bubbles, some of which are noise, in an Antarctic ice core.

Noise removal

Noise detection

Spatial point process

Parameter estimation

Markov chain Monte Carlo

Bayesian inference


Claudia Redenbach

Technische Universität Kaiserslautern

Aila Särkkä

Chalmers, Mathematical Sciences

Aila Särkkä

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Spatial Statistics

2211-6753 (ISSN)

Vol. 12 81-95

Driving Forces

Sustainable development

Subject Categories


Areas of Advance

Materials Science



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