238 citations · 300 across the 16 of their papers we have counts for
22 papers
Cox processes driven by transformed Gaussian processes on linear networks -- A review and new contributions
Jesper Møller, Jakob G. Rasmussen
There is a lack of point process models on linear networks. For an arbitrary linear network, we consider new models for a Cox process with an isotropic pair correlation function ob…
Determinantal shot noise Cox processes
Jesper Møller, Ninna Vihrs
We present a new class of cluster point process models, which we call determinantal shot noise Cox processes (DSNCP), with repulsion between cluster centres. They are the special c…
Fitting three-dimensional Laguerre tessellations by hierarchical marked point process models
Filip Seitl, Jesper Møller, Viktor Beneš
We present a general statistical methodology for analysing a Laguerre tessellation data set viewed as a realization of a marked point process model. In the first step, for the poin…
Should we condition on the number of points when modelling spatial point patterns?
Jesper Møller, Ninna Vihrs
We discuss the practice of directly or indirectly assuming a model for the number of points when modelling spatial point patterns even though it is rarely possible to validate such…
MCMC computations for Bayesian mixture models using repulsive point processes
Mario Beraha, Raffaele Argiento, Jesper Møller +1
Repulsive mixture models have recently gained popularity for Bayesian cluster detection. Compared to more traditional mixture models, repulsive mixture models produce a smaller num…
Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation
Ninna Vihrs, Jesper Møller, Alan E. Gelfand
In this paper, we propose a doubly stochastic spatial point process model with both aggregation and repulsion. This model combines the ideas behind Strauss processes and log Gaussi…