We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analysis. We use a data basis concerning public schools of the French Midi-Pyréenées region to illustrate the use of these exploratory techniques based on the coupling between a statistical graph and...

We introduce the hair-plot to visualize influential observations in dependent data. It consists of all trajectories of the value of an estimator when each observation is modified in turn by an additive perturbation. We define two measures of influence: the local influence which describes the...

We address the question of measuring and testing industrial spatial concentration based on micro-geographic data with distance based methods. We discuss the basic requirements for such measures and we propose four additional requirements. We also discuss the null assumptions classically used for...

We address the problem of prediction in the classical spatial autoregressive lag model for areal data. In contrast with the spatial econometrics literature, the geostatistical literature has devoted much attention to prediction using the Best Linear Unbiased Prediction approach. From the...

We explore the estimation of origin-destination (OD), city-pair, air passengers, in order to explicitly take into account spatial autocorrelation. To our knowledge, we are the …rst to test the presence of spatial autocorrelation and apply spatial econometric OD ow models to air transport....

To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and...