A compensator characterization of point processes on topological lattices.
A continuous-time model for claims reserving
Prediction of outstanding liabilities is an important problem in non-life insurance. In the framework of the Solvency II Project, the best estimate must be derived by well defined probabilistic models properly calibrated on the relevant claims experience. A general model along these lines was proposed earlier by Norberg (1993, 1999), who suggested modelling claim arrivals and payment streams as a marked point process. In this paper we specify that claims occur in [0,1] according to a Poisson point...
A deterministic displacement theorem for Poisson processes.
A dynamical characterization of Poisson-Dirichlet distributions.
A limit theorem for functionals of a Poisson process
A Markov regime-switching marked point process for short-rate analysis with credit risk.
A maximum likelihood estimator of an inhomogeneous Poisson point processes intensity using beta splines
The problem of estimating the intensity of a non-stationary Poisson point process arises in many applications. Besides non parametric solutions, e. g. kernel estimators, parametric methods based on maximum likelihood estimation are of interest. In the present paper we have developed an approach in which the parametric function is represented by two-dimensional beta-splines.
A note on discriminating Poisson processes from other point processes with stationary inter arrival times
We give a universal discrimination procedure for determining if a sample point drawn from an ergodic and stationary simple point process on the line with finite intensity comes from a homogeneous Poisson process with an unknown parameter. Presented with the sample on the interval the discrimination procedure , which is a function of the finite subsets of , will almost surely eventually stabilize on either POISSON or NOTPOISSON with the first alternative occurring if and only if the process is...
A note on limiting behaviour of disastrous environment exponents.
A note on the existence of Gibbs marked point processes with applications in stochastic geometry
This paper generalizes a recent existence result for infinite-volume marked Gibbs point processes. We try to use the existence theorem for two models from stochastic geometry. First, we show the existence of Gibbs facet processes in with repulsive interactions. We also prove that the finite-volume Gibbs facet processes with attractive interactions need not exist. Afterwards, we study Gibbs-Laguerre tessellations of . The mentioned existence result cannot be used, since one of its assumptions...
Adaptive estimation of the conditional intensity of marker-dependent counting processes
We propose in this work an original estimator of the conditional intensity of a marker-dependent counting process, that is, a counting process with covariates. We use model selection methods and provide a nonasymptotic bound for the risk of our estimator on a compact set. We show that our estimator reaches automatically a convergence rate over a functional class with a given (unknown) anisotropic regularity. Then, we prove a lower bound which establishes that this rate is optimal. Lastly, we provide...
An application of nonprarametric Cox regression model in reliability analysis: a case study
The contribution deals with an application of the nonparametric version of Cox regression model to the analysis and modeling of the failure rate of technical devices. The objective is to recall the method of statistical analysis of such a model, to adapt it to the real–case study, and in such a way to demonstrate the flexibility of the Cox model. The goodness-of-fit of the model is tested, too, with the aid of the graphical test procedure based on generalized residuals.
Anticipative calculus with respect to filtered Poisson processes
Anticipative direct transformations on the Poisson space
Asymptotic properties of the minimum contrast estimators for projections of inhomogeneous space-time shot-noise Cox processes
We consider a flexible class of space-time point process models—inhomogeneous shot-noise Cox point processes. They are suitable for modelling clustering phenomena, e.g. in epidemiology, seismology, etc. The particular structure of the model enables the use of projections to the spatial and temporal domain. They are used to formulate a step-wise estimation method to estimate different parts of the model separately. In the first step, the Poisson likelihood approach is used to estimate the inhomogeneity...
Asymptotics of certain coagulation-fragmentation processes and invariant Poisson-Dirichlet measures.