Denys Pommeret

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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)
Approximate Bayesian Computational (ABC) methods, or likelihood-free methods, have appeared in the past fifteen years as useful methods to perform Bayesian analysis when the likelihood is analytically or computationally intractable. Several ABC methods have been proposed: MCMC methods have been developed by Marjoram et al. [2003] and by Bortot et al. [2007](More)
This article describes the use of Markov chains to explore the time-patterns of antimicrobial exposure in broiler poultry. The transition in antimicrobial exposure status (exposed/not exposed to an antimicrobial, with a distinction between exposures to the different antimicrobial classes) in extensive data collected in broiler chicken flocks from November(More)
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 global moves, also called equi-energy jumps. The state space is partitioned into energy rings, and the current state of a chain can jump to a past state of an adjacent chain that has an energy level close to its level. This(More)
This letter is a response to the comments of Baragatti and Pommeret (2011) on Yang and Song (2010a) in Bioinformatics. Baragatti and Pommeret (2011) pointed out that in the case where the covariance matrix of the g-prior (Zellner, 1986) is singular, the computation of the posterior distributions proposed by Yang and Song (2010a) has a technical issue. In(More)
We consider the problem of missing data when the mechanism of missingness is not at random and when the partially observed variable has known or observed moments. A nonparametric estimator of the probability of missingness is proposed. A data driven statistic is constructed to test the missingness mechanism. Illustrations through univariate logistic(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 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)