Random effects compound Poisson model to represent data with extra zeros

This paper describes a compound Poisson-based random effects structure for modeling zero-inflated data. Data with large proportion of zeros are found in many fields of applied statistics, for example in ecology when trying to model and predict species counts (discrete data) or abundance distributions (continuous data). Standard methods for modeling such data include mixture and two-part conditional models. Conversely to these methods, the stochastic models proposed here behave coherently with regards to a change of scale, since they mimic the harvesting of a marked Poisson process in the modeling steps. Random effects are used to account for inhomogeneity. In this paper, model design and inference both rely on conditional thinking to understand the links between various layers of quantities : parameters, latent variables including random effects and zero-inflated observations. The potential of these parsimonious hierarchical models for zero-inflated data is exemplified using two marine macroinvertebrate abundance datasets from a large scale scientific bottom-trawl survey. The EM algorithm with a Monte Carlo step based on importance sampling is checked for this model structure on a simulated dataset : it proves to work well for parameter estimation but parameter values matter when re-assessing the actual coverage level of the confidence regions far from the asymptotic conditions.Comment: 4

Adaptive numerical designs for the calibration of computer codes

Making good predictions of a physical system using a computer code requires the inputs to be carefully specified. Some of these inputs called control variables have to reproduce physical conditions whereas other inputs, called parameters, are specific to the computer code and most often uncertain. The goal of statistical calibration consists in estimating these parameters with the help of a statistical model which links the code outputs with the field measurements. In a Bayesian setting, the posterior distribution of these parameters is normally sampled using MCMC methods. However, they are impractical when the code runs are high time-consuming. A way to circumvent this issue consists of replacing the computer code with a Gaussian process emulator, then sampling a cheap-to-evaluate posterior distribution based on it. Doing so, calibration is subject to an error which strongly depends on the numerical design of experiments used to fit the emulator. We aim at reducing this error by building a proper sequential design by means of the Expected Improvement criterion. Numerical illustrations in several dimensions assess the efficiency of such sequential strategies

Dissemination and geovisualization of territorial entities\u27 history

This paper describes an innovative solution for geovisualization of the demographic and administrative history of French municipalities named communes in French. This solution allows for the open dissemination of such data. The challenge is to provide a web interface for unskilled users in order to help them understand complex information about the demographic evolution of French territories. Our approach combines interactive thematic spatial and temporal views. We describe our architecture based on open-source technologies and the organization of this imperfect geo-historical information in our spatiotemporal database. Our second contribution concerns the concept of an acquaintance graph that has been used to obtain an efficient design with good performance in our geovisualization website

Caractérisation et évaluation de la virulence de souches cliniques de Clostridium perfringens chez le poulet à griller élevé sans antibiotique

réalisé en cotutelle avec Marie ArchambaultCette étude a développé un nouveau modèle aviaire de ligatures intestinales en boucles pour évaluer la virulence de souches de Clostridium perfringens causant l’entérite nécrotique chez le poulet. Des souches de C. perfringens caractérisées à partir d’une banque d’isolats récupérés de poulets à chair élevés sans antibiotique de fermes avec et sans problèmes d’entérite nécrotique ont été utilisées. La caractérisation des isolats de ces deux fermes a montré une faible diversité génétique parmi la ferme avec problèmes d’entérite nécrotique, alors que les isolats récupérés de la ferme sans entérite nécrotique a montré une haute diversité génétique. La détection de gènes de toxines a montré une prévalence de 95% pour le gène netB et 79% pour le gène cpb2 dans la ferme avec entérite nécrotique alors qu’elle était de 0% pour netB et 25% pour cpb2 dans la ferme sans entérite nécrotique. Dans le modèle de ligatures en boucles intestinales, les trois souches provenant de la ferme avec entérite nécrotique ont induit des lésions d’entérite nécrotique, alors que la souche provenant de la ferme sans entérite nécrotique a été incapable de reproduire l’entérite nécrotique. De plus, une souche netB négative et cpb2 positive provenant de la ferme avec entérite nécrotique a induit des lésions d’entérite nécrotique. Une association positive a aussi été observée entre la présence de lésions sévères et la localisation de larges bâtonnets à Gram-positif sur la muqueuse intestinale, suggérant que l’adhésion de C. perfringens à la muqueuse intestinale pourrait être importante dans la pathogénèse de l’entérite nécrotique. Ce modèle peut être utilisé pour étudier la virulence des souches de C. perfringens, en plus de montrer un fort potentiel pour étudier les interactions hôte-pathogène dans l’entérite nécrotique. Finalement, cette étude a montré que netB est un facteur de virulence important pour C. perfringens, mais non essentiel pour causer des lésions d’entérite nécrotique.This study developed a new avian intestinal ligated loop model to evaluate C. perfringens pathogenicity in chicken necrotic enteritis. C. perfringens strains were selected and characterized from a culture collection recovered from broiler chickens raised without antibiotic in farms with and without necrotic enteritis. Strain characterization showed a low genetic diversity in flocks with necrotic enteritis and genetic diversity was high in flocks without necrotic enteritis. Toxin gene detection showed a prevalence of 95% for netB and 79% for cpb2 in the farm with necrotic enteritis while prevalence was 0% for netB and 25% for cpb2 in the farm without necrotic enteritis. In the intestinal ligated loop model, the 3 strains recovered from the farm with necrotic enteritis produced necrotic enteritis lesions and the strain recovered from the farm without necrotic enteritis did not induce necrotic enteritis lesions. Also, a netB negative and cpb2 positive strain from the farm with necrotic enteritis induced lesions of necrotic enteritis. A positive association was also observed between severe necrotic enteritis lesions and the localization of large Gram-positive rods on intestinal mucosa, suggesting C. perfringens adherence to intestinal mucosa might be important in the pathogenesis of necrotic enteritis. This model can be used to study the virulence of C. perfringens strains while showing a high potential to study host-pathogen interactions in chicken necrotic enteritis. Finally, this study showed that netB can be an important factor in necrotic enteritis, but not essential to cause lesions of necrotic enteritis in chickens

Dating and localizing an invasion from post-introduction data and a coupled reaction-diffusion-absorption model

Invasion of new territories by alien organisms is of primary concern for environmental and health agencies and has been a core topic in mathematical modeling, in particular in the intents of reconstructing the past dynamics of the alien organisms and predicting their future spatial extents. Partial differential equations offer a rich and flexible modeling framework that has been applied to a large number of invasions. In this article, we are specifically interested in dating and localizing the introduction that led to an invasion using mathematical modeling, post-introduction data and an adequate statistical inference procedure. We adopt a mechanistic-statistical approach grounded on a coupled reaction-diffusion-absorption model representing the dynamics of an organism in an heterogeneous domain with respect to growth. Initial conditions (including the date and site of the introduction) and model parameters related to diffusion, reproduction and mortality are jointly estimated in the Bayesian framework by using an adaptive importance sampling algorithm. This framework is applied to the invasion of \textit{Xylella fastidiosa}, a phytopathogenic bacterium detected in South Corsica in 2015, France

Spatio-temporal modeling of avalanche frequencies in the French Alps

AbstractAvalanches threaten mountainous regions, and probabilistic long term hazard evaluation is a useful tool for land use planning and the definition of appropriate mitigation measures. This communication focuses on avalanches counts in the French Alps, and investigates their fluctuations in space and time within a Bayesian hierarchical modeling framework.We have at our disposal a 60 year data set covering the whole French Alps. The considered time scale is the winter. The elementary spatial scale is the township. It is small enough to allow information transfer between neighboring paths and large enough to avoid errors in paths localization. Data are standardized with a variable integrating the number of surveyed paths.A hierarchical Poisson-lognormal model appears well-adapted to depict the observation process with such discrete data. The spatial and temporal effects are assumed independent, and they are considered in the latent layer of the model. The temporal trend is modeled with a cubic spline whereas different spatial dependence sub-models are tested. The latter ones work on different types of supports (continuous field and discrete grid), and at different embedded spatial scales. Model inference and predictive sampling are carried out using Markov Chain Monte Carlo simulation methods. The spatial structure explains the larger part of the relative risks. The spatial dependence is visible at the scale of townships, but with a short range. At the larger scale of the massifs, the spatial dependence is weaker.The regional coherence of the results with the number of avalanche releases suggests that we may also search for other spatially structured variables implicated in the magnitude of avalanches that could help transfer information from one path to another