Gibbs point processes
Takacs-Fiksel method for stationary marked Gibbs point processes
... The rest of the paper is organized as follows. Section 2 introduces notation and a short background on marked Gibbs point processes. The Takacs-Fiksel method is presented in Section 3. It is based on ...
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Residuals and goodness-of-fit tests for stationary marked Gibbs point processes
... Poisson point process, but for general marked Gibbs point processes, the ex- isting validation methods are either graphical (for example by using the QQ-plot proposed ...
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Approximation intensity for pairwise interaction Gibbs point processes using determinantal point processes
... 2.2. Gibbs point processes For a recent and detailed presentation, we refer to Dereudre ( 2017 ...). Gibbs pro- cesses are characterized by an energy function H (or Hamiltonian) that maps any ...
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Consistency of likelihood estimation for Gibbs point processes
... of Gibbs point processes on R d ...of Gibbs interactions on a lattice, where consistency is established for most standard parametric models, regardless of the occurrence of phase transition ...
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Parametric estimation of pairwise Gibbs point processes with infinite range interaction
... discusses similar asymptotic results for the logistic regression estimator. The remainder of this paper is organized as follows. In Section 2 we recall some basic facts about Gibbs point processes ...
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Perfect Simulation of Determinantal Point Processes
... 1. Introduction Determinantal point process stems back from 1975 when O. Maachi introduce it as the ‘fermion’ process with repulsive feature on its points. It is only in the last two decades that Soshnikov(2000) ...
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Quantifying repulsiveness of determinantal point processes
... the Gibbs point processes. In contrast, for Gibbs point processes, no closed form expression is available for the moments, the likelihood involves an intractable normalizing ...
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Mixing properties and central limit theorem for associated point processes
... associated point processes are a class of point processes that induce attraction ...determinantal point processes (DPPs) are negatively ...spatial point processes ...
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Logarithmic, Coulomb and Riesz energy of point processes
... of having a point both at x and y. In this paper we will work with stationary random point processes such that ρ 1 ≡ 1 and we denote by P s,1 (X ) this set. 2.4 Dimension extension We recall some ...
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A tutorial on Palm distributions for spatial point processes
... for any non-negative measurable function h on S×N . For conditions ensuring that (18) holds, we refer to Ruelle (1969), Georgii (1988), or Dereudre et al. (2012). By the extensions of (6) and (12) to the general case, ...
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HIDDEN REGULAR VARIATION FOR POINT PROCESSES AND THE SINGLE/MULTIPLE LARGE POINT HEURISTIC
... for point processes. Point processes are an important tool in applied probability and stochastic modelling and are widely used in risk ...Lévy processes mentioned above can be seen as ...
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Stochastic analysis of point processes : beyond the Poisson process
... In this work, we are interested in what happens when self-healing is not sufficient. In case of serious disasters, the compensation from remaining nodes and traffic rerouting might not be sufficient to provide service ...
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Reciprocal processes. A measure-theoretical point of view
... VIEW CHRISTIAN L´ EONARD, SYLVIE RŒLLY, AND JEAN-CLAUDE ZAMBRINI Abstract. This is a survey paper about reciprocal processes. The bridges of a Markov process are also Markov. But an arbitrary mixture of these ...
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Lasso and probabilistic inequalities for multivariate point processes
... The classical framework consists in assuming that (X (m) , Y (m) , N (m) ) m=1,...,M is an i.i.d. M -sample and as for the Poisson model, it is natural to investigate asymptotic properties when M → +∞. If there are no ...
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Efficient Simulation of Sparse Graphs of Point Processes
... to point process models (dealing with events, directed graphs, continuous time, ...of point processes, prevented any direct ...a point process with respect to the discreteness of event-based ...
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Limit theorems for extreme value estimates of point processes boundaries
... Unité de recherche INRIA Rhône-Alpes 655, avenue de l’Europe - 38330 Montbonnot-St-Martin France Unité de recherche INRIA Lorraine : LORIA, Technopôle de Nancy-Brabois - Campus scientifi[r] ...
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Adaptive estimating function inference for non-stationary determinantal point processes
... determinantal point process the parameter would typically be a correlation scale parameter in the kernel of the de- terminantal point process, see Section 3 ...fitted point process model while [ 23 ] ...
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A concentration inequality for inhomogeneous Neymann-Scott point processes
... Neymann-Scott point process (NSPP for short), a class of models widely used in the literature to produce attractive ...Poisson point processes, each being concentrated similarly around its ...
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Asymptotic approximation of the likelihood of stationary determinantal point processes
... (with respect to the unit rate Poisson point process) is known since the seminal paper of Macchi (1975) [ 21 ]. But this expression is hardly tractable. It requires the knowledge of another kernel, usually called ...
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Extracting Geometric Structures in Images with Delaunay Point Processes
... Input scribbles [41] [41] + [37] [35] + [42] Ours Fig. 14. Visual comparisons with two-steps object contouring methods given different sets of input scribbles. The GrabCut pixel-based segmentation [41] requires many ...
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