Denys Pommeret

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The Equi-Energy Sampler (EES) introduced by Kou et al. [2006] is based on a population of chains which are updated by local moves and equi-energy jumps. This algorithm has been developed to facilitate global moves between the different chains, resulting in a good exploration of the states space by the target chain. This method seems to be more efficient(More)
In the Bayesian stochastic search variable selection framework, a common prior distribution for the regression coefficients is the g-prior of Zellner [1986]. However, there are two standard cases in which the associated covariance matrix does not exist, and the conventional prior of Zellner can not be used: if the number of observations is lower than the(More)
Consider two random variables contaminated by two unknown transformations. The aim of this paper is to test the equality of those transformations. Two cases are distinguished: first, the two random variables have known distributions. Second, they are unknown but observed before contaminations. We propose a nonparametric test statistic based on empirical(More)
In this paper we propose a smooth test of comparison for the marginal distributions of two possibly dependent strictly stationary sequences. We first state a general test procedure. Several cases of dependence are then investigated, allowing to cover various real situations. The test is applied to both simulated data and real datasets obtained from(More)
A numerical method to approximate ruin probabilities is proposed within the frame of a compound Poisson ruin model. The defective density function associated to the ruin probability is projected in an orthogonal polynomial system. These polynomials are orthogonal with respect to a probability measure that belongs to Natural Exponential Family with Quadratic(More)
In this paper we consider a random variable Y contamined by an independent additive noise Z. We assume that Z has known distribution. Our purpose is to test the distribution of the unobserved random variable Y. We propose a data driven statistic based on a development of the density of Y + Z, which is valid in the discrete case and in the continuous case.(More)