Poisson random effect panel data model is widely used in non-life insurance for posterior rate making. Recently, Lee et al. (2020) identify one shortcoming of the shared random effect assumption, which introduces both the marginal count distribution and the serial dependence between counts at...

French Abstract: Ce document de travail présente les méthodes d'estimation des paramètres d'un modèle de régression lorsque les variables sont observées sous un format intervalle. Il illustre cette procédure d'estimation sur les données de consommation d'électricité en France, afin...

In this paper, the relevance of national accounts statistics and their underlying conceptual framework is investigated for their four roles: description and object of analysis, tool for analysis and forecasting, tool for communication and decision-making and input for alternative accounts,...

Let k be a natural number and let G be a graph with at least k vertices. A.E. Brouwer conjectured that the sum of the k largest Laplacian eigenvalues of G is at most e(G) (k choose 2), where e(G) is the number of edges of G. We prove this conjecture for k = 2. We also show that if G is a tree,...

We study graphs with spectral radius at most $\frac{3}{2}\sqrt{2}$ and refine results by Woo and Neumaier [On graphs whose spectral radius is bounded by $\frac{3}{2}\sqrt{2}$, Graphs Combinatorics 23 (2007), 713-726]. We study the limit points of the spectral radii of certain families of graphs,...

Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis...

Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a 'robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by...

When building a Kriging model, the general intuition is that using more data will always result in a better model. However, we show that when we have a large non-uniform dataset, using a uniform subset can have several advantages. Reducing the time necessary to fit the model, avoiding numerical...