[PDF] Top 20 Moment formulae for general point processes
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Moment formulae for general point processes
... Introduction Point processes constitute a general framework used to model a wide variety of ...Poisson point process, which is one of the reasons for its use in a lot of practical ... Voir le document complet
17
Lasso and probabilistic inequalities for multivariate point processes
... inequalities for martin- ...results for multivariate Hawkes processes are proven, which allows us to check these assumptions by considering general dictionaries based on histograms, Fourier or ... Voir le document complet
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Takacs-Fiksel method for stationary marked Gibbs point processes
... very general setting, i.e. for a large class of stationary marked Gibbs models and test ...[24] for the Ising model and generalized to certain spatial point processes in ...the ... Voir le document complet
27
HIDDEN REGULAR VARIATION FOR POINT PROCESSES AND THE SINGLE/MULTIPLE LARGE POINT HEURISTIC
... erties 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 ... Voir le document complet
49
A tutorial on Palm distributions for spatial point processes
... . For conditions ensuring that (18) holds, we refer to Ruelle (1969), Georgii (1988), or Dereudre et ...the general case, (18) implies ρ(x) = Eλ(x, X). Unfortunately, in general it is not feasible to ... Voir le document complet
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Pseudolikelihood inference for Gibbsian T-tessellations ... and point processes
... 1 Introduction Recently, a new class of planar tessellations was introduced [12]: Gibbsian T- tessellations. Briefly, a T-tessellation is a tessellation with only vertices at the in- tersection of three edges, two of ... Voir le document complet
37
Bootstrap and permutation tests of independence for point processes
... problem for point ...rescaled general U -statistics, whose corresponding critical values are constructed from bootstrap and randomization/permutation approaches, making as few assumptions as possible ... Voir le document complet
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Pseudolikelihood inference for Gibbsian T-tessellations. . . and point processes
... 1 Introduction Recently, a new class of planar tessellations was introduced [12]: Gibbsian T- tessellations. Brie y, a T-tessellation is a tessellation with only vertices at the in- tersection of three edges, two of ... Voir le document complet
37
Adaptive estimating function inference for non-stationary determinantal point processes
... a general- ization of the stationary case Palm likelihood but the interpretation as a second-order composite likelihood given in [ 22 ] is more ...scope for simpler ... Voir le document complet
36
A concentration inequality for inhomogeneous Neymann-Scott point processes
... the general definition of inhomoge- neous ...convergence for innovation-type functionals in an increasing domain ...that for the Matérn cluster process and the Thomas process which are the two most ... Voir le document complet
12
Consistency of likelihood estimation for Gibbs point processes
... established for Gibbs measure generating very sparse point patterns, which implies restrictive conditions on the parameter ...[23]. For this example, the asymptotic law of the MLE is always Gaussian ... Voir le document complet
32
Mixing properties and central limit theorem for associated point processes
... a general central limit theorem (CLT) for random fields defined as a function of an associated point process (Theorem ...method for proving this kind of theorem is to rely on sufficiently fast ... Voir le document complet
24
Perfect Simulation of Determinantal Point Processes
... determinantal point pro- cesses and we provide a lower and a upper bound for the coalescence time in general ...a point process, including determinantal point process and its Papangelou ... Voir le document complet
16
Monte Carlo with Determinantal Point Processes
... determinantal point processes associated with multivariate orthogonal polynomials, and we obtain root mean square errors that decrease as N −(1+1/d)/2 , where d is the dimension of the ambient ...(CLT) ... Voir le document complet
49
Standard and robust intensity parameter estimation for stationary determinantal point processes
... λ for the class of stationary determinantal point ...properties for these two estimators have been established under general conditions on the underlying point ...mainly for Cox ... Voir le document complet
22
DPPy: Sampling Determinantal Point Processes with Python
... ) for a survey on exact ...a general-purpose toolbox on spatial point processes, includes sampling and learning of continuous DPPs with stationary kernels, as described by Lavancier et ... Voir le document complet
7
Conditional measures of generalized Ginibre point processes
... the general scheme, developed in [1], [3] for point processes on R, of the computation of conditional measures in intervals with respect to fixed exterior and relies on the results of [5] on ... Voir le document complet
28
Residuals and goodness-of-fit tests for stationary marked Gibbs point processes
... question for d −dimensional stationary marked Gibbs point pro- ...contexts for a large class of test functions ...very general and we show that they are fulfilled for several classical ... Voir le document complet
41
The allelic partition for coalescent point processes
... coalescent point process Splitting trees are those random trees where individuals give birth at constant rate b during a lifetime with general distribution Λ( ·)/b, to ... Voir le document complet
25
Contrast estimation for parametric stationary determinantal point processes
... theoretical point of view, neither the likelihood method nor the minimum contrast methods for DPPs have been studied thoroughly, even in assuming that a spectral method for C is ...the general ... Voir le document complet
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