A pairwise likelihood approach for the empirical estimation of the underlyingvariograms in the plurigaussian models

The plurigaussian model is particularly suited to describe categorical regionalized variables. Starting from a simple principle, the thresh-olding of one or several Gaussian random fields (GRFs) to obtain categories, the plurigaussian model is well adapted for a wide range ofsituations. By acting on the form of the thresholding rule and/or the threshold values (which can vary along space) and the variograms ofthe underlying GRFs, one can generate many spatial configurations for the categorical variables. One difficulty is to choose variogrammodel for the underlying GRFs. Indeed, these latter are hidden by the truncation and we only observe the simple and cross-variogramsof the category indicators. In this paper, we propose a semiparametric method based on the pairwise likelihood to estimate the empiricalvariogram of the GRFs. It provides an exploratory tool in order to choose a suitable model for each GRF and later to estimate its param-eters. We illustrate the efficiency of the method with a Monte-Carlo simulation study .The method presented in this paper is implemented in the R packageRGeostats.Comment: To be submitted to Spatial Statistic

Operational monitoring of radioelectric exposure in an urban environment

International audiencePolemics about base stations of cellular telephones have become a recurrent source of conflict among telecommunication companies, city authorities and citizens. Following early work performed within the framework of a doctoral thesis, the french research projet ANR Samper (2008-2011) has set up, for the first time, a network of monitoring stations in an urban environment, whose measurements are processed continuously by geostatistical methods, in order to inform daily the inhabitants on the hourly variations of radioelectric exposure in their surroundings. More precisely, the system uses a kriging of the exposure measurements including as external drift the output of a physical model of the propagation of the radioelectric signal emitted at different frequencies by the base stations. We present the implementation of the ANR Samper pre-operational monitoring system set up during several months in a section of the city of Grenoble

Efficient algorithms for calculating optimal designs in pharmacokinetics and dose finding studies

Random effects models are widely used in population pharmacokinetics and dose finding studies. In such models the presence of correlated observations (due to shared random effects and possibly residual serial correlation) usually makes the explicit determination of optimal designs diffcult. In this paper we develop a class of multiplicative algorithms for the numerical calculation of optimal experimental designs in such situations. In particular we demonstrate its application in a concrete example of a cross-over dose finding trial. Additionally, we show that the methodology can be modified to determine optimal designs where there exist some requirements regarding the minimal number of treatments for several (in some cases all) experimental conditions. AMS Subject Classi cation: 62K0

Joint modelling of repeated measurements and event time: Application to performance traits and survival of lambs bred in sub-humid tropics

We considered the analysis of a study for Dorper, Red Maasai and crossbred lambs born over a period of 6 years at the Diani Estate, Kenya. The study was designed to compare survival and performance traits of genotypes with differing susceptibilities to helminthiasis. The available data include information on time to death and repeated measurements of body weight, packed cell volume (PCV) and faecal egg count (FEC) of the animals. In the paper, we consider joint modelling of the survival time and the repeated measurements. Such an approach allows to account for the possible association between the survival and repeated measurement processes. The advantages and limitations of the joint modelling are discussed and illustrated using the Diani Estate study data

Retour d’expérience sur les apports du géographe dans l’observation des effets du changement climatique

L’adaptation au changement climatique constitue un défi sociétal dont le géographe doit s’emparer. Sa capacité d’appréhender le territoire et ses acteurs, ainsi que sa vision holistique, en font un interlocuteur privilégié des politiques publiques d’aménagement. A partir d’un retour d’expérience concernant la métropole lyonnaise, cette publication démontre le rôle joué par le géographe dans la structuration et l’innovation, selon une démarche intégrée et au sein d’une structure plurielle d’observation scientifique.Adaptation to climate change can be currently considered as a societal challenge that geographers must tackle. Their capacity to understand the territory and its actors, and their holistic vision, make them privileged partners of the public urban planners. This paper, concerning an ongoing project about the Greater Lyon, highlights the role of geographers in the structuration and innovation, according to an integrated process and within a plural scientific observation structure

Synthèse d'amides gras N-substitués par catalyse enzymatique

L'invention concerne un procédé de synthèse d'amides gras N-substitués par réaction d'un composé organique présentant une fonction acide terminale et un composé organique présentant une fonction amine terminale caractérisé en ce que ladite réaction est effectuée en présence d'une enzyme de la classe des acyltransférase